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Articles 6691 - 6720 of 9024
Full-Text Articles in Computer Sciences
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe
Tesla: An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Burcin Becerik-Gerber, Milind Tambe
Research Collection School Of Computing and Information Systems
This innovative application paper presents TESLA, an agent-based application for optimizing the energy use in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. TESLA provides three key contributions: (i) three online scheduling algorithms that consider flexibility of people’s preferences for energyefficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; and (iii) surveys of real users that indicate that TESLA’s assumptions exist in practice. TESLA was evaluated on data of over 110,000 meetings held …
Designing Leakage-Resilient Password Entry On Touchscreen Mobile Devices, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Designing Leakage-Resilient Password Entry On Touchscreen Mobile Devices, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
Touchscreen mobile devices are becoming commodities as the wide adoption of pervasive computing. These devices allow users to access various services at anytime and anywhere. In order to prevent unauthorized access to these services, passwords have been pervasively used in user authentication. However, password-based authentication has intrinsic weakness in password leakage. This threat could be more serious on mobile devices, as mobile devices are widely used in public places. Most prior research on improving leakage resilience of password entry focuses on desktop computers, where specific restrictions on mobile devices such as small screen size are usually not addressed. Meanwhile, additional …
R-Energy For Evaluating Robustness Of Dynamic Networks, Ming Gao, Ee Peng Lim, David Lo
R-Energy For Evaluating Robustness Of Dynamic Networks, Ming Gao, Ee Peng Lim, David Lo
Research Collection School Of Computing and Information Systems
The robustness of a network is determined by how well its vertices are connected to one another so as to keep the network strong and sustainable. As the network evolves its robustness changes and may reveal events as well as periodic trend patterns that affect the interactions among users in the network. In this paper, we develop R-energy as a new measure of network robustness based on the spectral analysis of normalized Laplacian matrix. R-energy can cope with disconnected networks, and is efficient to compute with a time complexity of O (jV j + jEj) where V and E are …
Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau
Distributed Gibbs: A Memory-Bounded Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Researchers have used distributed constraint optimization problems (DCOPs) to model various multi-agent coordination and resource allocation problems. Very recently, Ottens et al. proposed a promising new approach to solve DCOPs that is based on confidence bounds via their Distributed UCT (DUCT) sampling-based algorithm. Unfortunately, its memory requirement per agent is exponential in the number of agents in the problem, which prohibits it from scaling up to large problems. Thus, in this paper, we introduce a new sampling-based DCOP algorithm called Distributed Gibbs, whose memory requirements per agent is linear in the number of agents in the problem. Additionally, we show …
Demand Forecasting Using A Growth Model And Negative Binomial Regression Framework, Cally Yeru Ong, Murphy Choy, Michelle L. F. Cheong
Demand Forecasting Using A Growth Model And Negative Binomial Regression Framework, Cally Yeru Ong, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
In this paper, we look at demand forecasting by using a growth model and negative binomial regression framework. Using cumulative sales, we model the sales data for different wristwatch brands and relate it to their sales and growth characteristics. We apply clustering to determine the distinctive characteristics of each individual cluster. Four different growth models are applied to the clusters to find the most suitable growth model to be used. After determining the appropriate growth model to be applied, we then forecast the sales by applying the model to new products being launched in the market and continue to monitor …
Strong Location Privacy: A Case Study On Shortest Path Queries [Invited Paper], Kyriakos Mouratidis
Strong Location Privacy: A Case Study On Shortest Path Queries [Invited Paper], Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
The last few years have witnessed an increasing availability of location-based services (LBSs). Although particularly useful, such services raise serious privacy concerns. For example, exposing to a (potentially untrusted) LBS the client's position may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. There is a large body of work on protecting the location privacy of the clients. In this paper, we focus on shortest path queries, describe a framework based on private information retrieval (PIR), and conclude with open questions about the practicality of PIR and other location privacy approaches.
Vistruclizer: A Structural Visualizer For Multi-Dimensional Social Networks, Bingtian Dai, Agus Trisnajaya Kwee, Ee Peng Lim
Vistruclizer: A Structural Visualizer For Multi-Dimensional Social Networks, Bingtian Dai, Agus Trisnajaya Kwee, Ee Peng Lim
Research Collection School Of Computing and Information Systems
With the popularity of Web 2.0 sites, social networks today increasingly involve different kinds of relationships among different types of users in a single network. Such social networks are said to be multi-dimensional. Analyzing multi-dimensional networks is a challenging research task that requires intelligent visualization techniques. In this paper, we therefore propose a visual analytics tool called ViStruclizer to analyze structures embedded in a multi-dimensional social network. ViStruclizer incorporates structure analyzers that summarize social networks into both node clusters each representing a set of users, and edge clusters representing relationships between users in the node clusters. ViStruclizer supports user interactions …
Computer-Supported Collaborative Learning: A Research Framework, Yuan Long, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, Terrance Schoonover
Computer-Supported Collaborative Learning: A Research Framework, Yuan Long, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, Terrance Schoonover
Research Collection School Of Computing and Information Systems
Purpose - The purpose of this paper is to propose a computer-supported collaborative learning (CSCL) research framework. Design/methodology/approach - The framework was developed from a review and synthesis of the literature. More specifically, gaps in the literature were identified and a general framework for future CSCL research was proposed. Findings - This paper proposes a research framework that identifies a fit profile between learning objectives, learning tasks, and technology in CSCL. The fit profile, in turn, is expected to influence users' learning processes and outcomes. Research limitations/ implications - This framework can serve as a foundation for future research in …
Towards Omnidirectional Passive Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Yunhao Liu
Towards Omnidirectional Passive Human Detection, Zimu Zhou, Zheng Yang, Chenshu Wu, Longfei Shangguan, Yunhao Liu
Research Collection School Of Computing and Information Systems
Passive human detection and localization serve as key enablers for various pervasive applications such as smart space, human-computer interaction and asset security. The primary concern in devising scenario-tailored detecting systems is the coverage of their monitoring units. In conventional radio-based schemes, the basic unit tends to demonstrate a directional coverage, even if the underlying devices are all equipped with omnidirectional antennas. Such an inconsistency stems from the link-centric architecture, creating an anisotropic wireless propagating environment. To achieve an omnidirectional coverage while retaining the link-centric architecture, we propose the concept of Omnidirectional Passive Human Detection, and investigate to harness the PHY …
Information Security As A Credence Good, Ping Fan Ke, Kai-Lung Hui, Wei Thoo Yue
Information Security As A Credence Good, Ping Fan Ke, Kai-Lung Hui, Wei Thoo Yue
Research Collection School Of Computing and Information Systems
With increasing use of information systems, many organizations are outsourcing information security protection to a managed security service provider (MSSP). However, diagnosing the risk of an information system requires special expertise, which could be costly and difficult to acquire. The MSSP may exploit their professional advantage and provide fraudulent diagnosis of clients’ vulnerabilities. Such an incentive to mis-represent clients’ risks is often called the credence goods problem in the economics literature[3]. Although different mechanisms have been introduced to tackle the credence goods problem, in the information security outsourcing context, such mechanisms may not work well with the presence of system …
Predicting Sql Injection And Cross Site Scripting Vulnerabilities Through Mining Input Sanitization Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Predicting Sql Injection And Cross Site Scripting Vulnerabilities Through Mining Input Sanitization Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
ContextSQL injection (SQLI) and cross site scripting (XSS) are the two most common and serious web application vulnerabilities for the past decade. To mitigate these two security threats, many vulnerability detection approaches based on static and dynamic taint analysis techniques have been proposed. Alternatively, there are also vulnerability prediction approaches based on machine learning techniques, which showed that static code attributes such as code complexity measures are cheap and useful predictors. However, current prediction approaches target general vulnerabilities. And most of these approaches locate vulnerable code only at software component or file levels. Some approaches also involve process attributes that …
Circular Reranking For Visual Search, Ting Yao, Chong-Wah Ngo
Circular Reranking For Visual Search, Ting Yao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Search reranking is regarded as a common way to boost retrieval precision. The problem nevertheless is not trivial especially when there are multiple features or modalities to be considered for search, which often happens in image and video retrieval. This paper proposes a new reranking algorithm, named circular reranking, that reinforces the mutual exchange of information across multiple modalities for improving search performance, following the philosophy that strong performing modality could learn from weaker ones, while weak modality does benefit from interacting with stronger ones. Technically, circular reranking conducts multiple runs of random walks through exchanging the ranking scores among …
Enabling An Integrated Rate-Temporal Learning Scheme On Memristor, Wei He, Kejie Huang, Ning Ning, Kiruthika Ramanathan, Guoqi Li, Yu Jiang, Jiayin Sze, Luping Shi, Rong Zhao, Jing Pei
Enabling An Integrated Rate-Temporal Learning Scheme On Memristor, Wei He, Kejie Huang, Ning Ning, Kiruthika Ramanathan, Guoqi Li, Yu Jiang, Jiayin Sze, Luping Shi, Rong Zhao, Jing Pei
Research Collection School Of Computing and Information Systems
Learning scheme is the key to the utilization of spike-based computation and the emulation of neural/synaptic behaviors toward realization of cognition. The biological observations reveal an integrated spike time- and spike rate-dependent plasticity as a function of presynaptic firing frequency. However, this integrated rate-temporal learning scheme has not been realized on any nano devices. In this paper, such scheme is successfully demonstrated on a memristor. Great robustness against the spiking rate fluctuation is achieved by waveform engineering with the aid of good analog properties exhibited by the iron oxide-based memristor. The spike-time-dependence plasticity (STDP) occurs at moderate presynaptic firing frequencies …
Searching Visual Instances With Topology Checking And Context Modeling, Wei Zhang, Chong-Wah Ngo
Searching Visual Instances With Topology Checking And Context Modeling, Wei Zhang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Instance Search (INS) is a realistic problem initiated by TRECVID, which is to retrieve all occurrences of the querying object, location, or person from a large video collection. It is a fundamental problem with many applications, and also a challenging problem different from the traditional concept or near-duplicate (ND) search, since the relevancy is defined at instance level. True responses could exhibit various visual variations, such as being small on the image with different background, or showing a non-homography spatial configuration. Based on the Bag-of-Words model, we propose two techniques tailored for Instance Search. Specifically, we explore the use of …
Delayed Insertion And Rule Effect Moderation Of Domain Knowledge For Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Delayed Insertion And Rule Effect Moderation Of Domain Knowledge For Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Though not a fundamental pre-requisite to efficient machine learning, insertion of domain knowledge into adaptive virtual agent is nonetheless known to improve learning efficiency and reduce model complexity. Conventionally, domain knowledge is inserted prior to learning. Despite being effective, such approach may not always be feasible. Firstly, the effect of domain knowledge is assumed and can be inaccurate. Also, domain knowledge may not be available prior to learning. In addition, the insertion of domain knowledge can frame learning and hamper the discovery of more effective knowledge. Therefore, this work advances the use of domain knowledge by proposing to delay the …
Roundtriprank: Graph-Based Proximity With Importance And Specificity, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Roundtriprank: Graph-Based Proximity With Importance And Specificity, Yuan Fang, Kevin Chen-Chuan Chang, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Graph-based proximity has many applications with different ranking needs. However, most previous works only stress the sense of importance by finding "popular” results for a query. Often times important results are overly general without being well-tailored to the query, lacking a sense of specificity— which only emerges recently. Even then, the two senses are treated independently, and only combined empirically. In this paper, we generalize the well-studied importance-based random walk into a round trip and develop RoundTripRank, seamlessly integrating specificity and importance in one coherent process. We also recognize the need for a flexible trade-off between the two senses, and …
Finding The Optimal Social Trust Path For The Selection Of Trustworthy Service Providers In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim
Finding The Optimal Social Trust Path For The Selection Of Trustworthy Service Providers In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Online social networks have provided the infrastructure for a number of emerging applications in recent years, e.g., for the recommendation of service providers or the recommendation of files as services. In these applications, trust is one of the most important factors in decision making by a service consumer, requiring the evaluation of the trustworthiness of a service provider along the social trust paths from a service consumer to the service provider. However, there are usually many social trust paths between two participants who are unknown to one another. In addition, some social information, such as social relationships between participants and …
Arraytrack: A Fine-Grained Indoor Location System, Jie Xiong, Kyle Jamieson
Arraytrack: A Fine-Grained Indoor Location System, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
With myriad augmented reality, social networking, and retail shopping applications all on the horizon for the mobile handheld, a fast and accurate location technology will become key to a rich user experience. When roaming outdoors, users can usually count on a clear GPS signal for accurate location, but indoors, GPS often fades, and so up until recently, mobiles have had to rely mainly on rather coarse-grained signal strength readings. What has changed this status quo is the recent trend of dramatically increasing numbers of antennas at the indoor access point, mainly to bolster capacity and coverage with multiple-input, multiple-output (MIMO) …
Cross-Domain Password-Based Authenticated Key Exchange Revisited, Liqun Chen, Hoon Wei Lim, Guomin Yang
Cross-Domain Password-Based Authenticated Key Exchange Revisited, Liqun Chen, Hoon Wei Lim, Guomin Yang
Research Collection School Of Computing and Information Systems
We revisit the problem of secure cross-domain communication between two users belonging to different security domains within an open and distributed environment. Existing approaches presuppose that either the users are in possession of public key certificates issued by a trusted certificate authority (CA), or the associated domain authentication servers share a long-term secret key. In this paper, we propose a generic framework for designing four-party password-based authenticated key exchange (4PAKE) protocols. Our framework takes a different approach from previous work. The users are not required to have public key certificates, but they simply reuse their login passwords they share with …
Modeling Social Information Learning Among Taxi Drivers, Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel Ni
Modeling Social Information Learning Among Taxi Drivers, Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel Ni
Research Collection School Of Computing and Information Systems
When a taxi driver of an unoccupied taxi is seeking passengers on a road unknown to him or her in a large city, what should the driver do? Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows (e.g., hotel taxi rank)? This is an interesting problem that arises everyday in many cities worldwide. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood …
Beta Atomic Contacts: Identifying Critical Specific Contacts In Protein Binding Interfaces, Qian Lu, Chee Keong Kwoh, Steven C. H. Hoi
Beta Atomic Contacts: Identifying Critical Specific Contacts In Protein Binding Interfaces, Qian Lu, Chee Keong Kwoh, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the …
Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance, Ling Liu, Daniel Q. Chen, Nan Hu, Indranil Bose, Garry D. Bruton
Core Versus Peripheral Information Technology Employees And Their Impact On Firm Performance, Ling Liu, Daniel Q. Chen, Nan Hu, Indranil Bose, Garry D. Bruton
Research Collection School Of Computing and Information Systems
Scholars have widely argued, but not previously examined, that core employees with firm specific skills are critical to the firm's strategic success. This argument has led to the belief that employees whose skills are not firm specific can be readily replaced in the external market and are peripheral to the firm's strategic goals. Employing a resource based view of the firm, we find that the core information technology (IT) employees with firm specific skills are value-adding resources that aid the firm's performance whereas peripheral employees with less firm specific skills provide no value to the firm's performance. Examining the issue …
Twicube: A Real-Time Twitter Online Community Analysis Tool, Juan Du, Wei Xie, Cheng Li, Feida Zhu, Ee Peng Lim
Twicube: A Real-Time Twitter Online Community Analysis Tool, Juan Du, Wei Xie, Cheng Li, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
As a micro-blogging service, Twitter differs from other social network services in two ways: 1) the absence of mutual consent in establishing follow links and 2) being a mixture of news media and social network. A key question to ask in better understanding Twitter user behavior is which part of a user’s Twitter network reflects one’s real-life social network. TwiCube is an online tool that employs a novel algorithm capable of identifying a user’s real-life social community, which we call the user’s off-line community, purely from examining the link structure among the user’s followers and followees. Based on the identified …
Dynamic Label Propagation In Social Networks, Juan Du, Feida Zhu, Ee Peng Lim
Dynamic Label Propagation In Social Networks, Juan Du, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Label propagation has been studied for many years, starting from a set of nodes with labels and then propagating to those without labels. In social networks, building complete user profiles like interests and affiliations contributes to the systems like link prediction, personalized feeding, etc. Since the labels for each user are mostly not filled, we often employ some people to label these users. And therefore, the cost of human labeling is high if the data set is large. To reduce the expense, we need to select the optimal data set for labeling, which produces the best propagation result. In this …
Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.3.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Stephane Glondu
Deckard - A Tree-Based, Scalable, And Accurate Code Clone Detection Tool (Version 1.3.1), Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Stephane Glondu
SMU Research Data
Deckard is a tree-based, scalable, and accurate code clone detection tool. It is also capable of reporting clone-related bugs. For more information, pls refer to readme.txt. The latest version is available from Deckard repository on Github. https://github.com/skyhover/Deckard
Network Structure Of Social Coding In Github, Ferdian Thung, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Network Structure Of Social Coding In Github, Ferdian Thung, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Social coding enables a different experience of software development as the activities and interests of one developer are easily advertized to other developers. Developers can thus track the activities relevant to various projects in one umbrella site. Such a major change in collaborative software development makes an investigation of networkings on social coding sites valuable. Furthermore, project hosting platforms promoting this development paradigm have been thriving, among which GitHub has arguably gained the most momentum. In this paper, we contribute to the body of knowledge on social coding by investigating the network structure of social coding in GitHub. We collect …
Robust Image Analysis With Sparse Representation On Quantized Visual Features, Bingkun Bao, Guangyu Zhu, Jialie Shen, Shuicheng Yan
Robust Image Analysis With Sparse Representation On Quantized Visual Features, Bingkun Bao, Guangyu Zhu, Jialie Shen, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Recent techniques based on Sparse Representation (SR) have demonstrated promising performance on high-level visual recognition, exemplified by the high-accuracy face recognition under occlusions and other sparse corruptions [1]. Most research in this area has focused on classification algorithms using raw image pixels, and very few have been proposed to utilize the quantized visual features, such as the popular Bagof- Words (BOW) feature abstraction. In such cases, besides the inherent quantization errors, ambiguity associated with visual word assignment and mis-detection of feature points due to factors such as visual occlusions and noises, constitutes the major causes to the dense corruptions of …
A Self-Training Framework For Automatic Identification Of Exploratory Dialogue, Zhongyu Wei, Yulan He, Simon Shum, Rebecca Ferguson, Wei Gao, Kam-Fai Wong
A Self-Training Framework For Automatic Identification Of Exploratory Dialogue, Zhongyu Wei, Yulan He, Simon Shum, Rebecca Ferguson, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
The dramatic increase in online learning materials over the last decade has made it difficult for individuals to locate information they need. Until now, researchers in the field of Learning Analytics have had to rely on the use of manual approaches to identify exploratory dialogue. This type of dialogue is desirable in online learning environments, since training learners to use it has been shown to improve learning outcomes. In this paper, we frame the problem of exploratory dialogue detection as a binary classification task, classifying a given contribution to an online dialogue as exploratory or non-exploratory. We propose a self-training …
Almost Touching: Parent-Child Remote Communication Using The Sharetable System, Svetlana Yarosh, Anthony Tang, Sanika Mokashi, Gregory D. Abowd
Almost Touching: Parent-Child Remote Communication Using The Sharetable System, Svetlana Yarosh, Anthony Tang, Sanika Mokashi, Gregory D. Abowd
Research Collection School Of Computing and Information Systems
We deployed the ShareTable - a system that provides easy-to-initiate videochat and a shared tabletop task space - in four divorced households. Throughout the month of its use, the families employed the ShareTable to participate in shared activities, share emotional moments, and communicate closeness through metaphorical touch. The ShareTable provided a number of advantages over the phone and was easier to use than standard videoconferencing. However, it did also introduce concerns over privacy and new sources of conflict about appropriate calling practices. We relate our findings to the larger research landscape and present implications for future work.
Data Visualization On Interactive Surfaces: A Research Agenda, Petra Isenberg, Tobias Isenberg, Tobias Hesselmann, Bongshin Lee, Ulrich Von Zadow, Anthony Tang
Data Visualization On Interactive Surfaces: A Research Agenda, Petra Isenberg, Tobias Isenberg, Tobias Hesselmann, Bongshin Lee, Ulrich Von Zadow, Anthony Tang
Research Collection School Of Computing and Information Systems
Interactive tabletops and surfaces (ITSs) provide rich opportunities for data visualization and analysis and consequently are used increasingly in such settings. A research agenda of some of the most pressing challenges related to visualization on ITSs emerged from discussions with researchers and practitioners in human-computer interaction, computer-supported collaborative work, and a variety of visualization fields at the 2011 Workshop on Data Exploration for Interactive Surfaces (Dexis 2011)