Computer Sciences Commons^™

Artificial Intelligence-Enhanced Predictive Insights For Advancing Financial Inclusion: A Human-Centric Ai-Thinking Approach, Meng Leong How, Sin Mei Cheah, Aik Cheow Khor, Yong Jiet Chan

Research Collection Lee Kong Chian School Of Business

According to the World Bank, a key factor to poverty reduction and improving prosperity is financial inclusion. Financial service providers (FSPs) offering financially-inclusive solutions need to understand how to approach the underserved successfully. The application of artificial intelligence (AI) on legacy data can help FSPs to anticipate how prospective customers may respond when they are approached. However, it remains challenging for FSPs who are not well-versed in computer programming to implement AI projects. This paper proffers a no-coding human-centric AI-based approach to simulate the possible dynamics between the financial profiles of prospective customers collected from 45,211 contact encounters and predict …

Google Summer Of Code: Student Motivations And Contributions, Jefferson O. Silva, Igor Scaliante Wiese, Daniel M. Germán, Christoph Treude, Marco Aurélio Gerosa, Igor Steinmacher

Research Collection School Of Computing and Information Systems

Several open source software (OSS) projects participate in engagement programs like Summers of Code expecting to foster newcomers’ onboarding and receive contributions. However, scant empirical evidence identifies why students join such programs. In this paper, we study the well-established Google Summer of Code (GSoC), which is a 3-month OSS engagement program that offers stipends and mentorship to students willing to contribute to OSS projects. We combined a survey (of students and mentors) and interviews (of students) to understand what motivates students to enter GSoC. Our results show that students enter GSoC for an enriching experience, and not necessarily to become …

Poster Abstract: Data Communication Using Switchable Privacy Glass, Changshuo Hu, Dong Ma, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

Switchable privacy glass can electronically change its state between opaque and transparent. In this work, we propose to exploit the electronic configurability of switchable glass to modulate natural light, which can be demodulated by a nearby receiver with light sensing capability to realise data communication over natural light. A key advantage is that no energy is used to generate light, as it simply modulates the existing light in the nature. We demonstrate that the proposed data communication using switchable glass modulation can achieve 33.33 bits per second communication with a bit rate below 1% under a wide range of ambient …

Identity-Based Encryption Transformation For Flexible Sharing Of Encrypted Data In Public Cloud, Robert H. Deng, Zheng Qin, Qianhong Wu, Zhenyu Guan, Robert H. Deng, Yujue Wang, Yunya Zhou

Research Collection School Of Computing and Information Systems

With the rapid development of cloud computing, an increasing number of individuals and organizations are sharing data in the public cloud. To protect the privacy of data stored in the cloud, a data owner usually encrypts his data in such a way that certain designated data users can decrypt the data. This raises a serious problem when the encrypted data needs to be shared to more people beyond those initially designated by the data owner. To address this problem, we introduce and formalize an identity-based encryption transformation (IBET) model by seamlessly integrating two well-established encryption mechanisms, namely identity-basedencryption (IBE) and …

Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Reverse logistics has been implemented by various companies because of its ability to gain more profit and maintain the competitiveness of the company. However, extensive studies on the vehicle routing problem with cross-docking (VRPCD) only considered the forward flow instead of the reverse flow. Motivated by the ability of a VRPCD network to minimize the distribution cost in the forward flow, this research incorporates the reverse logistics scheme in a VRPCD network, namely the VRP with reverse cross-docking (VRP-RCD). We propose a VRP-RCD mathematical model for a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. The main …

How To And How Much? Teaching Ethics In An Interaction Design Course, Bimlesh Wadhwa, Eng Lieh Ouh, Benjamin Gan

Research Collection School Of Computing and Information Systems

How much is sufficient and how should one teach ethics in an Interaction Design curriculum in undergraduate computing program has been a point of dilemma for many HCI educators. We conducted a preliminary study using a mixed method to gather perception on ethics in our interaction design courses at two of the leading Singapore Universities. We answer three research questions specific to an undergraduate HCI course: Is there a need for ethics? Is there sufficient ethics coverage? and how to teach ethics? We surveyed 140 students and interviewed six teachers in two Singapore Universities. Our findings suggest that 92% of …

A New Construction For Linkable Secret Handshake, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Guomin Yang, Zheng Yang

Research Collection School Of Computing and Information Systems

In this paper, we introduce a new construction for linkable secret handshake that allows authenticated users to perform handshake anonymously within allowable times. We define formal security models for the new construction, and prove that it can achieve session key security, anonymity, untraceability and linkable affiliation-hiding. In particular, the proposed construction ensures that (i) anyone can trace the real identities of dishonest users who perform handshakes for more than k times; and (ii) an optimal communication cost between authorized users is achieved by exploiting the proof of knowledges.

Privacy-Preserving Outsourced Support Vector Machine Design For Secure Drug Discovery, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for privacy-preserving outsourced drug discovery in the cloud, which we refer to as POD. Specifically, POD is designed to allow the cloud to securely use multiple drug formula providers' drug formulas to train Support Vector Machine (SVM) provided by the analytical model provider. In our approach, we design secure computation protocols to allow the cloud server to perform commonly used integer and fraction computations. To securely train the SVM, we design a secure SVM parameter selection protocol to select two SVM parameters and construct a secure sequential minimal optimization protocol to privately refresh …

Voicecoach: Interactive Evidence-Based Training For Voice Modulation Skills In Public Speaking, Xingbo Wang, Haipeng Zeng, Yong Wang, Aoyu Wu, Zhida Sun, Xiaojuan Ma, Qu Huamin

Research Collection School Of Computing and Information Systems

The modulation of voice properties, such as pitch, volume, and speed, is crucial for delivering a successful public speech. However, it is challenging to master different voice modulation skills. Though many guidelines are available, they are often not practical enough to be applied in different public speaking situations, especially for novice speakers. We present VoiceCoach, an interactive evidence-based approach to facilitate the effective training of voice modulation skills. Specifically, we have analyzed the voice modulation skills from 2623 high-quality speeches (i.e., TED Talks) and use them as the benchmark dataset. Given a voice input, VoiceCoach automatically recommends good voice modulation …

Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu

Research Collection School Of Computing and Information Systems

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users’ demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model …

Using Knowledge Bases For Question Answering, Yunshi Lan

Dissertations and Theses Collection (Open Access)

A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.

In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …

Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing provides an efficient and convenient platform for cloud users to store, process and control their data. Cloud overcomes the bottlenecks of resource-constrained user devices and greatly releases their storage and computing burdens. However, due to the lack of full trust in cloud service providers, the cloud users generally prefer to outsource their sensitive data in an encrypted form, which, however, seriously complicates data processing, analysis, as well as access control. Homomorphic encryption (HE) as a single key system cannot flexibly control data sharing and access after encrypted data processing. How to realize various computations over encrypted data in …

Ifix: Fixing Concurrency Bugs While They Are Introduced, Zan Wang, Haichi Wang, Shuang Liu, Jun Sun, Haoyu Wang, Junjie Chen

Research Collection School Of Computing and Information Systems

Concurrency bugs are notoriously hard to identify and fix. A systematic way of avoiding concurrency bugs is to design and implement a locking policy that consistently guards all shared variables. Concurrency bugs thus can be viewed as the result of an illy-designed or poorly implemented locking policy. The trouble is that the locking policy is often not documented, which makes debugging concurrency bugs clueless. We argue that it is too late to debug concurrency bugs after programming is done and we instead detect and fix them while they are being implemented. In this work, we propose an approach named IFIX …

Automatic Verification Of Multi-Threaded Programs By Inference Of Rely-Guarantee Specifications, Xuan-Bach Le, David Sanan, Jun Sun, Shang-Wei Lin

Research Collection School Of Computing and Information Systems

Rely-Guarantee is a comprehensive technique that supports compositional reasoning for concurrent programs. However, specifications of the Rely condition - environment interference, and Guarantee condition - local transformation of thread state - are challenging to establish. Thus the construction of these conditions becomes bottleneck in automating the technique. To tackle the above problem, we propose a verification framework that, based on Rely-Guarantee principles, constructs the correctness proof of concurrent program through inferring suitable Rely -Guarantee conditions automatically. Our framework first constructs a Hoare-style sequential proof for each thread and then applies abstraction refinement to elevate these proofs into concurrent ones with …

An Empirical Study On Correlation Between Coverage And Robustness For Deep Neural Networks, Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jinsong Dong, Ting Dai

Research Collection School Of Computing and Information Systems

Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs are subject to attacks such as adversarial perturbation and thus must be properly tested. Many coverage criteria for DNN since have been proposed, inspired by the success of code coverage criteria for software programs. The expectation is that if a DNN is well tested (and retrained) according to such coverage criteria, it is more likely to be robust. In this work, we conduct an empirical study to evaluate the relationship between coverage, robustness and …

When The Bank Comes To You: Branch Network And Customer Omnichannel Banking Behavior, Mi Zhou, Dan Geng, Vibhanshu Abhishek, Beibei Li

Research Collection School Of Computing and Information Systems

Banks today have been increasingly reducing their physical presence and redirecting customers to digital channels, and yet, the consequences of this strategy are not well studied. This paper investigates the effects of banks' branch network changes (i.e., branch openings and branch closures) on customer omnichannel banking behavior. Using approximately 0.85 million (33 months') anonymized individual-level banking transactions from a large commercial bank in the United States, this paper shows the asymmetric effects of branch openings and branch closures on customer omnichannel banking behavior. In particular, we find that branch openings increase customers' branch transactions; however, the first branch opening leads …

Towards K-Vertex Connected Component Discovery From Large Networks, Li Yuan, Guoren Wang, Yuhai Zhao, Feida Zhu

Research Collection School Of Computing and Information Systems

In many real life network-based applications such as social relation analysis, Web analysis, collaborative network, road network and bioinformatics, the discovery of components with high connectivity is an important problem. In particular, k-edge connected component (k-ECC) has recently been extensively studied to discover disjoint components. Yet many real scenarios present more needs and challenges for overlapping components. In this paper, we propose a k-vertex connected component (k-VCC) model, which is much more cohesive, and thus supports overlapping between components very well. To discover k-VCCs, we propose three frameworks including top-down, bottom-up and hybrid …

Learning Fault Models Of Cyber Physical Systems, Teck Ping Khoo, Jun Sun, Sudipta Chattopadhyay

Research Collection School Of Computing and Information Systems

Cyber Physical Systems (CPSs) comprise sensors and actuators which interact with the physical environment over a computer network to achieve some control objective. Bugs in CPSs can have severe consequences as CPSs are increasingly deployed in safety-critical applications. Debugging CPSs is therefore an important real world problem. Traces from a CPS can be lengthy and are usually linked to different parts of the system, making debugging CPSs a complex and time-consuming undertaking. It is challenging to isolate a component without running the whole CPS. In this work, we propose a model-based approach to debugging a CPS. For each CPS property, …

Using Reinforcement Learning To Minimize The Probability Of Delay Occurrence In Transportation, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhengghua Chen, Le Zhang, Xuexi Zhang

Research Collection School Of Computing and Information Systems

Reducing traffic delay is of crucial importance for the development of sustainable transportation systems, which is a challenging task in the studies of stochastic shortest path (SSP) problem. Existing methods based on the probability tail model to solve the SSP problem, seek for the path that minimizes the probability of delay occurrence, which is equal to maximizing the probability of reaching the destination before a deadline (i.e., arriving on time). However, they suffer from low accuracy or high computational cost. Therefore, we design a novel and practical Q-learning approach where the converged Q-values have the practical meaning as the actual …

Capacitor-Based Activity Sensing For Kinetic-Powered Wearable Iots, Guohao Lan, Dong Ma, Weitao Xu, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

We propose the use of the conventional energy storage component, i.e., capacitor, in the kinetic-powered wearable IoTs as the sensor to detect human activities. Since activities accumulate energy in the capacitor at different rates, the charging rate of the capacitor can be used to detect the activities. The key advantage of the proposed capacitor-based activity sensing mechanism, called CapSense, is that it obviates the need for sampling the motion signal at a high rate, and thus, significantly reduces power consumption of the wearable device. The challenge we face is that capacitors are inherently non-linear energy accumulators, which leads to significant …

Securing Bring-Your-Own-Device (Byod) Programming Exams, Oka Kurniawan, Norman Lee, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Traditional pen and paper exams are inadequate for modern university programming courses as they are misaligned with pedagogies and learning objectives that target practical coding ability. Unfortunately, many institutions lack the resources or space to be able to run assessments in dedicated computer labs. This has motivated the development of bring-your-own-device (BYOD) exam formats, allowing students to program in a similar environment to how they learnt, but presenting instructors with significant additional challenges in preventing plagiarism and cheating. In this paper, we describe a BYOD exam solution based on lockdown browsers, software which temporarily turns students' laptops into secure workstations …

Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu

Research Collection School Of Computing and Information Systems

Recent years have witnessed promising results of exploring deep convolutional neural network for face detection. Despite making remarkable progress, face detection in the wild remains challenging especially when detecting faces at vastly different scales and characteristics. In this paper, we propose a novel simple yet effective framework of “Feature Agglomeration Networks” (FANet) to build a new single-stage face detector, which not only achieves state-of-the-art performance but also runs efficiently. As inspired by Feature Pyramid Networks (FPN) (Lin et al., 2017), the key idea of our framework is to exploit inherent multi-scale features of a single convolutional neural network by aggregating …

W8-Scope: Fine-Grained, Practical Monitoring Of Weight Stack-Based Exercises, Meeralakshmi Radhakrishnan, Archan Misra, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Fine-grained, unobtrusive monitoring of gym exercises can help users track their own exercise routines and also provide corrective feedback. We propose W8-Scope, a system that uses a simple magnetic-cum-accelerometer sensor, mounted on the weight stack of gym exercise machines, to infer various attributes of gym exercise behavior. More specifically, using multiple machine learning models, W8-Scope helps identify who is exercising, what exercise she is doing, how much weight she is lifting, and whether she is committing any common mistakes. Real world studies, conducted with 50 subjects performing 14 different exercises over 103 distinct sessions in two gyms, show that W8-Scope …

Detecting Fake News In Social Media: An Asia-Pacific Perspective, Meeyoung Cha, Wei Gao, Cheng-Te Li

Research Collection School Of Computing and Information Systems

In March 2011, the catastrophic accident known as "The Fukushima Daiichi nuclear disaster" took place, initiated by the Tohoku earthquake and tsunami in Japan. The only nuclear accident to receive a Level-7 classification on the International Nuclear Event Scale since the Chernobyl nuclear power plant disaster in 1986, the Fukushima event triggered global concerns and rumors regarding radiation leaks. Among the false rumors was an image, which had been described as a map of radioactive discharge emanating into the Pacific Ocean, as illustrated in the accompanying figure. In fact, this figure, depicting the wave height of the tsunami that followed, …

Pokeme: Applying Context-Driven Notifications To Increase Worker Engagement In Mobile Crowd-Sourcing, Thivya Kandappu, Abhinav Mehrotra, Archan Misra, Mirco Musolesi, Shih-Fen Cheng, Lakmal Buddika Meegahapola

Research Collection School Of Computing and Information Systems

In mobile crowd-sourcing systems, simply relying on people to opportunistically select and perform tasks typically leads to drawbacks such as low task acceptance/completion rates and undesirable spatial skews. In this paper, we utilize data from "Smart Campus", a campus-based mobile crowd-sourcing platform, to empirically study and discover whether and how various context-aware notification strategies can help overcome such drawbacks. We first study worker interactions, in the absence of any notifications, to discover some spatio-temporal properties of task acceptance and completion. Based on these insights, we then experimentally demonstrate the effectiveness of two novel, non-personal, context-driven notification strategies, comparing the outcomes …

Automated Synthesis Of Local Time Requirement For Service Composition, Étienne André, Tian Huat Tan, Manman Chen, Shuang Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Service composition aims at achieving a business goal by composing existing service-based applications or components. The response time of a service is crucial, especially in time-critical business environments, which is often stated as a clause in service-level agreements between service providers and service users. To meet the guaranteed response time requirement of a composite service, it is important to select a feasible set of component services such that their response time will collectively satisfy the response time requirement of the composite service. In this work, we use the BPEL modeling language that aims at specifying Web services. We extend it …

Space Efficient Revocable Ibe For Mobile Devices In Cloud Computing, Baodong Qin, Ximeng Liu, Zhuo Wei, Dong Zheng

Research Collection School Of Computing and Information Systems

Revocation capacity is one of the main properties for an identity-based encryption (IBE), as in practice users’ private keys are possibly leaked or expired. However, existing revocable IBE schemes usually lack of short keys. Recently, Lin et al. proposed a method to design space efficient revocable IBE scheme from non-monotonic key-policy attribute-based encryption scheme. But, it requires too many pairings (linear to the number of revoked users) to decrypt an IBE ciphertext. In this study, we overcome this problem by adopting the technique of server-aided revocation, recently proposed by Qin et al. in ESORICS 2015. The main contribution is a …

The Spatial Optimization And Evaluation Of The Economic, Ecological, And Social Value Of Urban Green Space In Shenzhen, Yuhan Yu, Wenting Zhang, Peihong Fu, Wei Huang, Keke Li, Kai Cao

Research Collection School Of Computing and Information Systems

Urban green space (UGS) is important in urban systems, as it benefits economic development, ecological conservation, and living conditions. Many studies have evaluated the economic, ecological, and social value of UGS worldwide, and spatial optimization for UGS has been carried out to maximize its value. However, few studies have simultaneously examined these three values of UGS in one optimization system. To fill this gap, this study evaluated the economic value of UGS in terms of promoting housing prices, its ecological value through the relief of high land surface temperature (LST), and its social value through the provision of recreation spaces …

S2n2: An Interpretive Semantic Structure Attention Neural Network For Trajectory Classification, Canghong Jin, Ting Tao, Xianzhe Luo, Zemin Liu, Minghui Wu

Research Collection School Of Computing and Information Systems

We have witnessed a rapid growth over past decades in sensor data mining (SDM), which aims at extracting valuable information automatically from large repositories of moving activity data. One of the significant SDM tasks is identifying humans through their transit modes using a variety of user-tracking systems. However, to the best of our knowledge, distinguishing traces of users and understanding their behaviors are difficult tasks in most real-life cases for the following reasons: 1) activity data containing both temporal and spatial contexts are of high order and sparse; 2) living patterns are not as regular as expected, and the route …

Understanding Wikipedia As A Resource For Opportunistic Learning Of Computing Concepts, Martin P. Robillard, Christoph Treude

Research Collection School Of Computing and Information Systems

Posts on on-line forums where programmers look for information often include links to Wikipedia when it can be assumed the reader will not be familiar with the linked terms. A Wikipedia article will thus often be the first exposure to a new computing concept for a novice programmer. We conducted an exploratory study with 18 novice programmers by asking them to read a Wikipedia article on a common computing concept that was new to them, while using the think-aloud protocol. We performed a qualitative analysis of the session transcripts to better understand the experience of the novice programmer learning a …