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Articles 6031 - 6060 of 8479
Full-Text Articles in Computer Sciences
Creating Adaptive Quests To Support Personalized Learning Experiences When Learning Software Languages, Chris Boesch, Sandra Boesch
Creating Adaptive Quests To Support Personalized Learning Experiences When Learning Software Languages, Chris Boesch, Sandra Boesch
Research Collection School Of Computing and Information Systems
Over the past three years the authors have been developing and refining an online practicing platform called SingPath, which enables users to practice writing code in various software languages. The most recent feature to be released is a Quest mode that encourages users by showing short video clips each time a user solves five problems. In addition, users are able to choose whether to play through these quests on easy, medium, or hard levels of difficulty. The ability for users to customize their game play enables them to modify the difficulty of the experience and ideally self-regulate how frustrating or …
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Automatic Recovery Of Root Causes From Bug-Fixing Changes, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
No abstract provided.
A Unified Model For Topics, Events And Users On Twitter, Qiming Diao, Jing Jiang
A Unified Model For Topics, Events And Users On Twitter, Qiming Diao, Jing Jiang
Research Collection School Of Computing and Information Systems
With the rapid growth of social media, Twitter has become one of the most widely adopted platforms for people to post short and instant message. On the one hand, people tweets about their daily lives, and on the other hand, when major events happen, people also follow and tweet about them. Moreover, people’s posting behaviors on events are often closely tied to their personal interests. In this paper, we try to model topics, events and users on Twitter in a unified way. We propose a model which combines an LDA-like topic model and the Recurrent Chinese Restaurant Process to capture …
Learning Topics And Positions From Debatepedia, Swapna Gottopati, Minghui Qiu, Yanchuan Sim, Jing Jiang, Noah Smith
Learning Topics And Positions From Debatepedia, Swapna Gottopati, Minghui Qiu, Yanchuan Sim, Jing Jiang, Noah Smith
Research Collection School Of Computing and Information Systems
We explore Debatepedia, a communityauthored encyclopedia of sociopolitical debates, as evidence for inferring a lowdimensional, human-interpretable representation in the domain of issues and positions. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opinion words. We evaluate the resulting representation’s usefulness in attaching opinionated documents to arguments and its consistency with human judgments about positions.
Modeling Interaction Features For Debate Side Clustering, Minghui Qiu, Liu Yang, Jing Jiang
Modeling Interaction Features For Debate Side Clustering, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
Online discussion forums are popular social media platforms for users to express their opinions and discuss controversial issues with each other. To automatically identify the sides/stances of posts or users from textual content in forums is an important task to help mine online opinions. To tackle the task, it is important to exploit user posts that implicitly contain support and dispute (interaction) information. The challenge we face is how to mine such interaction information from the content of posts and how to use them to help identify stances. This paper proposes a two-stage solution based on latent variable models: an …
Livelabs: Initial Reflections On Building A Large-Scale Mobile Behavioral Experimentation Testbed, Archan Misra, Rajesh Krishna Balan
Livelabs: Initial Reflections On Building A Large-Scale Mobile Behavioral Experimentation Testbed, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
We believe that, for successful adoption of novel mobile technologies and applications, it is important to be able to test them under real usage patterns, and with real users. To implement this vision, we present our initial effort in building LiveLabs, a large-scale mobile testbed for in-situ experimentation. LiveLabs is unique in two aspects. First, LiveLabs operates on a scale much larger than most research testbeds— it is being deployed in four different public spaces in Singapore (a university campus, a shopping mall, an airport and a leisure resort), and is expected to have a pool of over 30,000 opt-in …
Predictive Handling Of Asynchronous Concept Drifts In Distributed Environments, Hock Hee Ang, Vivek Gopalkrishnan, Indre Zliobaite, Mykola Pechenizkiy, Steven C. H. Hoi
Predictive Handling Of Asynchronous Concept Drifts In Distributed Environments, Hock Hee Ang, Vivek Gopalkrishnan, Indre Zliobaite, Mykola Pechenizkiy, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In a distributed computing environment, peers collaboratively learn to classify concepts of interest from each other. When external changes happen and their concepts drift, the peers should adapt to avoid increase in misclassification errors. The problem of adaptation becomes more difficult when the changes are asynchronous, i.e., when peers experience drifts at different times. We address this problem by developing an ensemble approach, PINE, that combines reactive adaptation via drift detection, and proactive handling of upcoming changes via early warning and adaptation across the peers. With empirical study on simulated and real-world data sets, we show that PINE handles asynchronous …
Online Multimodal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Hao Xia, Peilin Zhao, Dayong Wang, Chunyan Miao
Online Multimodal Distance Metric Learning With Application To Image Retrieval, Pengcheng Wu, Steven C. H. Hoi, Hao Xia, Peilin Zhao, Dayong Wang, Chunyan Miao
Research Collection School Of Computing and Information Systems
Recent years have witnessed extensive studies on distance metric learning (DML) for improving similarity search in multimedia information retrieval tasks. Despite their successes, most existing DML methods suffer from two critical limitations: (i) they typically attempt to learn a linear distance function on the input feature space, in which the assumption of linearity limits their capacity of measuring the similarity on complex patterns in real-world applications; (ii) they are often designed for learning distance metrics on uni-modal data, which may not effectively handle the similarity measures for multimedia objects with multimodal representations. To address these limitations, in this paper, we …
Online Multi-Task Collaborative Filtering For On-The-Fly Recommender Systems, Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Zhi-Yong Liu
Online Multi-Task Collaborative Filtering For On-The-Fly Recommender Systems, Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training data arrives, which is clearly non-scalable for large real recommender systems where users' rating data often arrives sequentially and frequently. In this paper, we investigate a novel efficient and scalable online collaborative filtering technique for on-the-fly recommender systems, which is able to effectively online update the recommendation model from a sequence of rating observations. Specifically, we …
On Effects Of Visual Query Complexity, Jialie Shen, Cheng Zhiyong
On Effects Of Visual Query Complexity, Jialie Shen, Cheng Zhiyong
Research Collection School Of Computing and Information Systems
As an effective technique to manage large scale image collections, content-based image retrieval (CBIR) has been received great attentions and became a very active research domain in recent years. While assessing system performance is one of the key factors for the related technological advancement, relatively little attention has been paid to model and analyze test queries. This paper documents a study on the problem of determining visual query complexity as a measure for predicting image retrieval performance. We propose a quantitative metric for measuring complexity of image queries for content-based image search engine. A set of experiments are carried out …
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Clustering Algorithms For Maximizing The Lifetime Of Wireless Sensor Networks With Energy-Harvesting Sensors, Pengfei Zhang, Gaoxi Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Motivated by recent developments in wireless sensor networks (WSNs), we present several efficient clustering algorithms for maximizing the lifetime of WSNs, i.e., the duration till a certain percentage of the nodes die. Specifically, an optimization algorithm is proposed for maximizing the lifetime of a single-cluster network, followed by an extension to handle multi-cluster networks. Then we study the joint problem of prolonging network lifetime by introducing energy-harvesting (EH) nodes. An algorithm is proposed for maximizing the network lifetime where EH nodes serve as dedicated relay nodes for cluster heads (CHs). Theoretical analysis and extensive simulation results show that the proposed …
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
An Experimental Study For Inter-User Interference Mitigation In Wireless Body Sensor Networks, Bin Cao, Yu Ge, Chee Wee Kim, Gang Feng, Hwee-Pink Tan, Yun Li
Research Collection School Of Computing and Information Systems
Inter-user interference degrades the reliability of data delivery in wireless body sensor networks (WBSNs) in dense deployments when multiple users wearing WBSNs are in close proximity to one another. The impact of such interference in realistic WBSN systems is significant but is not well explored. To this end, we investigate and analyze the impact of inter-user interference on packet delivery ratio (PDR) and throughput. We conduct extensive experiments based on the TelosB WBSN platform, considering unslotted carrier sense multiple access (CSMA) with collision avoidance (CA) and slotted CSMA/CA modes in IEEE 802.15.4 MAC, respectively. In order to mitigate interuser interference, …
A Collusion-Resistant Conditional Access System For Flexible-Pay-Per-Channel Pay-Tv Broadcasting, Zhiguo Wan, June Liu, Rui Zhang, Robert H. Deng
A Collusion-Resistant Conditional Access System For Flexible-Pay-Per-Channel Pay-Tv Broadcasting, Zhiguo Wan, June Liu, Rui Zhang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Pay-TV Broadcasting system, an extensively de- ployed application, charges its subscribers when receiving the broadcasted video. A conditional access system (CAS) ensures security for the Pay-TV broadcasting system, which is designed to control TV channel/program access to only authorized subscribers. There are mainly three CAS models: pay-per-channel (PPC), pay-per-view (PPV), and flexible-pay-per-channel (F- PPC). F-PPC is a novel model which combines the properties and advantages of both PPC and PPV. Several key management schemes with four-level hierarchical key structure have been proposed for this model. In this paper, we point out a severe security weakness of these schemes against collusion …
The Myths Of G-Tech For Business Decision Making, Tin Seong Kam
The Myths Of G-Tech For Business Decision Making, Tin Seong Kam
Research Collection School Of Computing and Information Systems
More than 80% of organisation data are location related - the locations where transactions are done, where retailers are found, and of customers who buy their products. Since the early 2005, there has been an increasing interest among the business community to use geospatial technology to enhance decision making process at both strategic and operational levels. Millions of dollars and man-hours have been invested into driving their geo-technology development and implementation. The use of geospatial technology in business, however, tends to confine to simple mapping. Many of these failures are the victims of misperception. Some of the perpetrators are practitioners. …
Riga: A Rich Internet Geospatial Analytics Application For Area-Based Data, Tin Seong Kam
Riga: A Rich Internet Geospatial Analytics Application For Area-Based Data, Tin Seong Kam
Research Collection School Of Computing and Information Systems
In this information age, more and more public statistical data such as population census, household living, local economy and business establishment are distributed over the internet within the framework of spatial data infrastructure. By and large, these data are organized geographically such as region, province as well as district. Usually, they are published in the form of digital maps over the internet as simple points, lines and polygons markers limited or no analytical function available to transform these data into useful information. To meet the analytical needs of casual public data users, we contribute RIGA, a rich internet geospatial analytics …
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Research Collection School Of Computing and Information Systems
This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.
Learning Spatio-Temporal Co-Occurrence Correlograms For Efficient Human Action Classification, Qianru Sun, Hong Liu
Learning Spatio-Temporal Co-Occurrence Correlograms For Efficient Human Action Classification, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Spatio-temporal interest point (STIP) based features show great promises in human action analysis with high efficiency and robustness. However, they typically focus on bag-of-visual words (BoVW), which omits any correlation among words and shows limited discrimination in real-world videos. In this paper, we propose a novel approach to add the spatio-temporal co-occurrence relationships of visual words to BoVW for a richer representation. Rather than assigning a particular scale on videos, we adopt the normalized google-like distance (NGLD) to measure the words' co-occurrence semantics, which grasps the videos' structure information in a statistical way. All pairwise distances in spatial and temporal …
Inferring Ongoing Human Activities Based On Recurrent Self-Organizing Map Trajectory, Qianru Sun, Hong Liu
Inferring Ongoing Human Activities Based On Recurrent Self-Organizing Map Trajectory, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Automatically inferring ongoing activities is to enable the early recognition of unfinished activities, which is quite meaningful for applications, such as online human-machine interaction and security monitoring. State-of-the-art methods use the spatiotemporal interest point (STIP) based features as the low-level video description to handle complex scenes. While the existing problem is that typical bag-of-visual words (BoVW) focuses on the statistical distribution of features but ignores the inherent contexts in activity sequences, resulting in low discrimination when directly dealing with limited observations. To solve this problem, the Recurrent Self-Organizing Map (RSOM), which was designed to process sequential data, is novelly adopted …
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
A Highly Efficient Rfid Distance Bounding Protocol Without Real-Time Prf Evaluation, Yunhui Zhuang, Anjia Yang, Duncan S. Wong, Guomin Yang, Qi Xie
Research Collection School Of Computing and Information Systems
There is a common situation among current distance bounding protocols in the literature: they set the fast bit exchange phase after a slow phase in which the nonces for both the reader and a tag are exchanged. The output computed in the slow phase is acting as the responses in the subsequent fast phase. Due to the calculation constrained RFID environment of being lightweight and efficient, it is the important objective of building the protocol which can have fewer number of message flows and less number of cryptographic operations in real time performed by the tag. In this paper, we …
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
Research Collection School Of Computing and Information Systems
This paper investigates the value relevance of accounting information in the presence of ineffective internal control (IIC). Based on Ohlson's valuation model, this paper first documents that IIC can directly affect a firm's market value after control cost of capital, corporate governance, and other, value-relevant variables. Second, this paper finds that the value relevance of earnings and book value in determining a firm's market value are significantly reduced. Collectively, the results of this paper indicate that the effectiveness of internal controls can directly affect a firm's market value and the value relevance of accounting information.
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we present the design and implementation of Focus, a system for effectively and efficiently reducing power consumption of OLED displays on smartphones. These displays, while becoming exceedingly common still consume significant power. The key idea of Focus is that we use the notion of saliency to save display power by dimming portions of the applications that are less important to the user. We envision Focus being especially useful during low battery situations when usability is less important than power savings. We tested Focus using 15 applications running on a Samsung Galaxy S III and show that it …
Driverguard: Virtualization Based Fine-Grained Protection On I/O Flows, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Driverguard: Virtualization Based Fine-Grained Protection On I/O Flows, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
Most commodity peripheral devices and their drivers are geared to achieve high performance with security functions being opted out. The absence of strong security measures invites attacks on the I/O data and consequently posts threats to those services feeding on them, such as fingerprint-based biometric authentication. In this article, we present a generic solution called DriverGuard, which dynamically protects the secrecy of I/O flows such that the I/O data are not exposed to the malicious kernel. Our design leverages a composite of cryptographic and virtualization techniques to achieve fine-grained protection without using any extra devices and modifications on user applications. …
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of a participatory sensing paradigm, where data generated from individual smartphones is used to extract and understand collective properties of temporary public gatherings and events (e.g., concerts & conferences). We focus on the use of this paradigm at a technical conference, and describe the design, implementation and deployment of ConferenceSense, an application that uses multiple sensor and human-generated inputs from attendees' smartphones to infer context, such as the start time of a session or the degree of interaction during a tea break. Based on data collected from multiple attendees at a 3-day conference, we explore how …
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
Science and Technology Parks are in the business of providing services to their tenants, a mix of large companies, Small and Medium Enterprises and startups. The service needs of each of these types of companies will be different. The quality of services can be improved by understanding the needs of the tenants both, prior to building the Science and Technology Parks as well as on an ongoing basis. This paper introduces the CUGAR model for Science and Technology Parks as well as Service Innovation Design framework. It then proceeds to discuss how the Service Innovation framework could be applied to …
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
Research Collection School Of Computing and Information Systems
Debugging is a crucial yet expensive activity to improve the reliability of software systems. To reduce debugging cost, various fault localization tools have been proposed. A spectrum-based fault localization tool often outputs an ordered list of program elements sorted based on their likelihood to be the root cause of a set of failures (i.e., their suspiciousness scores). Despite the many studies on fault localization, unfortunately, however, for many bugs, the root causes are often low in the ordered list. This potentially causes developers to distrust fault localization tools. Recently, Parnin and Orso highlight in their user study that many debuggers …
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Spectrum-based fault localization refers to the process of identifying program units that are buggy from two sets of execution traces: normal traces and faulty traces. These approaches use statistical formulas to measure the suspiciousness of program units based on the execution traces. There have been many spectrum-based fault localization approaches proposing various formulas in the literature. Two of the best performing and well-known ones are Tarantula and Ochiai. Recently, Xie et al. find that theoretically, under certain assumptions, two families of spectrum-based fault localization formulas outperform all other formulas including those of Tarantula and Ochiai. In this work, we empirically …
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
Research Collection School Of Computing and Information Systems
In modern society, more and more people are suffering from some type of stress. Monitoring and timely detecting of stress level will be very valuable for the person to take counter measures. In this paper, we investigate the use of decision analytics methodologies to detect stress. We present a new feature selection method based on the principal component analysis (PCA), compare three feature selection methods, and evaluate five information fusion methods for stress detection. A driving stress data set created by the MIT Media lab is used to evaluate the relative performance of these methods. Our study show that the …
An Analysis Of Post-Selection In Automatic Configuration, Zhi Yuan, Thomas St\303\274tzle, Marco A. Montes De Oca, Hoong Chuin Lau, Mauro Birattari
An Analysis Of Post-Selection In Automatic Configuration, Zhi Yuan, Thomas St\303\274tzle, Marco A. Montes De Oca, Hoong Chuin Lau, Mauro Birattari
Research Collection School Of Computing and Information Systems
Automated algorithm configuration methods have proven to be instrumental in deriving high-performing algorithms and such methods are increasingly often used to configure evolutionary algorithms. One major challenge in devising automatic algorithm configuration techniques is to handle the inherent stochasticity in the configuration problems. This article analyses a post-selection mechanism that can also be used for this task. The central idea of the post-selection mechanism is to generate in a first phase a set of high-quality candidate algorithm configurations and then to select in a second phase from this candidate set the (statistically) best configuration. Our analysis of this mechanism indicates …
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense …
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Users face many choices on the Web when it comes to choosing which product to buy, which video to watch, etc. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users’ item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: whether the items adopted by a user correlate to items adopted by her friends, and …