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Full-Text Articles in Entire DC Network
A Passive Testing Approach For Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee Xian Tan, Hwee-Pink Tan, Zhangbing Zhou
A Passive Testing Approach For Protocols In Wireless Sensor Networks, Xiaoping Che, Stephane Maag, Hwee Xian Tan, Hwee-Pink Tan, Zhangbing Zhou
Research Collection School Of Computing and Information Systems
Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed for wireless sensor networks (WSN). However, one stage that is often neglected before their deployment is the conformance testing process, a cruicial and challenging step. Compared to active testing techniques commonly used in wired networks, passive approaches are more suitable to the WSN environment. While some works …
Stack Layout Randomization With Minimal Rewriting Of Android Binaries, Yu Liang, Xinjie Ma, Daoyuan Wu, Xiaoxiao Tang, Debin Gao, Guojun Peng, Chunfu Jia, Huanguo Zhang
Stack Layout Randomization With Minimal Rewriting Of Android Binaries, Yu Liang, Xinjie Ma, Daoyuan Wu, Xiaoxiao Tang, Debin Gao, Guojun Peng, Chunfu Jia, Huanguo Zhang
Research Collection School Of Computing and Information Systems
Stack-based attacks typically require that attackers have a good understanding of the stack layout of the victim program. In this paper, we leverage specific features on ARM architecture and propose a practical technique that introduces randomness to the stack layout when an Android application executes. We employ minimal binary rewriting on the Android app that produces randomized executable of the same size which can be executed on an unmodified Android operating system. Our experiments on applying this randomization on the most popular 20 free Android apps on Google Play show that the randomization coverage of functions increases from 65% (by …
Cost-Sensitive Online Classification With Adaptive Regularization And Its Applications, Peilin Zhao, Furen Zhuang, Min Wu, Xiao-Li Li, Hoi, Steven C. H.
Cost-Sensitive Online Classification With Adaptive Regularization And Its Applications, Peilin Zhao, Furen Zhuang, Min Wu, Xiao-Li Li, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
Cost-Sensitive Online Classification is recently proposed to directly online optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. However, the previous existing learning algorithms only utilized the first order information of the data stream. This is insufficient, as recent studies have proved that incorporating second order information could yield significant improvements on the prediction model. Hence, we propose a novel cost-sensitive online classification algorithm with adaptive regularization. We theoretically analyzed the proposed algorithm and empirically validated its effectiveness with extensive experiments. We also demonstrate the application of the …
Cnl: Collective Network Linkage Across Heterogeneous Social Platforms, Ming Gao, Ee-Peng Lim, David Lo, Feida Zhu, Philips Kokoh Prasetyo, Aoying Zhou
Cnl: Collective Network Linkage Across Heterogeneous Social Platforms, Ming Gao, Ee-Peng Lim, David Lo, Feida Zhu, Philips Kokoh Prasetyo, Aoying Zhou
Research Collection School Of Computing and Information Systems
The popularity of social media has led many users to create accounts with different online social networks. Identifying these multiple accounts belonging to same user is of critical importance to user profiling, community detection, user behavior understanding and product recommendation. Nevertheless, linking users across heterogeneous social networks is challenging due to large network sizes, heterogeneous user attributes and behaviors in different networks, and noises in user generated data. In this paper, we propose an unsupervised method, Collective Network Linkage (CNL), to link users across heterogeneous social networks. CNL incorporates heterogeneous attributes and social features unique to social network users, handles …
Experience Report: An Industrial Experience Report On Test Outsourcing Practices, Xin Xia, David Lo, Pavneet Singh Kochhar, Zhenchang Xing, Xinyu Wang, Shanping Li
Experience Report: An Industrial Experience Report On Test Outsourcing Practices, Xin Xia, David Lo, Pavneet Singh Kochhar, Zhenchang Xing, Xinyu Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Nowadays, many companies contract their testing functionalities out to third-party IT outsourcing companies. This process referred to as test outsourcing is common in the industry, yet it is rarely studied in the research community. In this paper, to bridge the gap, we performed an empirical study on test outsourcing with 10 interviewees and 140 survey respondents. We investigated various research questions such as the types, the process, and the challenges of test outsourcing, and the differences between test outsourcing and in-house testing. We found customer satisfaction, tight project schedule, and domain unfamiliarity are the top-3 challenges faced by the testers. …
Should Fixing These Failures Be Delegated To Automated Program Repair?, Le Dinh Xuan Bach, Le Bui Tien Duy, David Lo
Should Fixing These Failures Be Delegated To Automated Program Repair?, Le Dinh Xuan Bach, Le Bui Tien Duy, David Lo
Research Collection School Of Computing and Information Systems
Program repair constitutes one of the major components of software maintenance that usually incurs a significant cost in software production. Automated program repair is supposed to help in reducing the software maintenance cost by automatically fixing software defects. Despite the recent advances in automated software repair, it is still very costly to wait for repair tools to produce valid repairs of defects. This paper addresses the following question: "Will an automated program repair technique find a repair for a defect within a reasonable time?". To answer this question, we build an oracle that can predict whether fixing a failure should …
Not All Trips Are Equal: Analyzing Foursquare Check-Ins Of Trips And City Visitors, Wen Haw Chong, Bingtian Dai, Ee Peng Lim
Not All Trips Are Equal: Analyzing Foursquare Check-Ins Of Trips And City Visitors, Wen Haw Chong, Bingtian Dai, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Location-Based Social Networks (LBSN) such as Foursquare allow users to indicate venue visits via check-ins. This results in much fine grained context-rich data, useful for studying user mobility. In this work, we use check-ins to characterize trips and visitors to two cities, where visitors are defined as having their home cities elsewhere. First, we divide trips into two duration types: long and short. We then show that trip types differ in check-in distributions over venue categories, time slots, as well as check-in intensity. Based on the trip types, we then divide visitors into long-term and short-term visitors. We compare visitor …
Real-Time Detection Of Seat Occupancy And Hogging, Huy Hoang Nguyen, Nakul Gulati, Youngki Lee, Rajesh Krishna Balan
Real-Time Detection Of Seat Occupancy And Hogging, Huy Hoang Nguyen, Nakul Gulati, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we propose a cheap and effective solution to detect if specific seats at a shared public table are occupied -- either by humans or by objects (i.e., the seats are being "hogged"). The hogging of seats, in particular, is a big problem for our campus library and required a large amount of manpower to correct (to find and clear hogged seats). We propose using two different cheap sensors, a capacitance sensor and an infrared (IR) sensor, to solve this problem. In the rest of this paper, we show how using these sensors can accurately determine if a …
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Modelling Cascades Over Time In Microblogs, Xie Wei, Feida Zhu, Siyuan Liu, Ke Wang
Research Collection School Of Computing and Information Systems
One of the most important features of microblogging services such as Twitter is how easy it is to re-share a piece of information across the network through various user connections, forming what we call a "cascade". Business applications such as viral marketing have driven a tremendous amount of research effort predicting whether a certain cascade will go viral. Yet the rarity of viral cascades in real data poses a challenge to all existing prediction methods. One solution is to simulate cascades that well fit the real viral ones, which requires our ability to tell how a certain cascade grows over …
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Analysis Of Aspects And Star Ratings In Consumer Reviews, Maruthi Prithivirajan, Vivian Lai, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
This paper presents an analysis of star ratings in consumer reviews in Yelp, an online social platform for sharing consumer reviews about local businesses. In particular, we analyze consumer reviews about food businesses. We analyze how well or poorly the star ratings (on a scale of one star to five stars) associated with these reviews tally with the sentiment derived from the textual portion of the consumer review.
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Security And Privacy Of Electronic Health Information Systems: Editorial, Elisa Bertino, Robert H. Deng, Xinyi Huang, Jianying Zhou
Research Collection School Of Computing and Information Systems
Digital technologies have dramatically transformed our daily lives by bringing countless conveniences and benefits. As an evolving concept, electronic health information has become the focus of attention in both academia and industry. By leveraging modern digital technologies like the internet and the cloud, electronic health information systems will be a key enabling technology in improving the quality and convenience of patient care, encouraging patient participation in their care, reducing medical errors, improving practice efficiencies, and saving time and cost. The complexity of electronic health information systems, however, raises several new security and privacy issues. It is thus critical to investigate …
Interpolation Guided Compositional Verification, Shang-Wei Lin, Jun Sun, Truong Khanh Nguyen, Yang Liu, Jin Song Dong
Interpolation Guided Compositional Verification, Shang-Wei Lin, Jun Sun, Truong Khanh Nguyen, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Model checking suffers from the state space explosion problem. Compositional verification techniques such as assume-guarantee reasoning (AGR) have been proposed to alleviate the problem. However, there are at least three challenges in applying AGR. Firstly, given a system M1 M2, how do we automatically construct and refine (in the presence of spurious counterexamples) an assumption A2, which must be an abstraction of M2? Previous approaches suggest to incrementally learn and modify the assumption through multiple invocations of a model checker, which could be often time consuming. Secondly, how do we keep the state space small when checking M1 A2 |= …
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Automating The Performance Deviation Analysis For Multiple System Releases: An Evolutionary Study, Felipe Pinto, Uirá Kulesza, Christoph Treude
Research Collection School Of Computing and Information Systems
This paper presents a scenario-based approach for the evaluation of the quality attribute of performance, measured in terms of execution time (response time). The approach is implemented by a framework that uses dynamic analysis and repository mining techniques to provide an automated way for revealing potential sources of performance degradation of scenarios between releases of a software system. The approach defines four phases: (i) preparation – choosing the scenarios and preparing the target releases; (ii) dynamic analysis – determining the performance of scenarios and methods by calculating their execution time; (iii) degradation analysis – processing and comparing the results of …
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Stability Of Transportation Networks Under Adaptive Routing Policies, Sebastien Boyer, Sebastien Blandin, Laura Wynter
Research Collection School Of Computing and Information Systems
Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, much fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic …
Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo
Deep Multimodal Learning For Affective Analysis And Retrieval, Lei Pang, Shiai Zhu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Social media has been a convenient platform for voicing opinions through posting messages, ranging from tweeting a short text to uploading a media file, or any combination of messages. Understanding the perceived emotions inherently underlying these user-generated contents (UGC) could bring light to emerging applications such as advertising and media analytics. Existing research efforts on affective computation are mostly dedicated to single media, either text captions or visual content. Few attempts for combined analysis of multiple media are made, despite that emotion can be viewed as an expression of multimodal experience. In this paper, we explore the learning of highly …
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Using Gamification As A Collaboration Motivator For Software Development Teams: A Preliminary Framework, Flavio Steffens, Sabrina Marczak, Fernando Figueira Filho, Christoph Treude, Leif Singer, David Redmiles, Ban Al-Ani
Research Collection School Of Computing and Information Systems
Gamification is the use of game elements in non-game context to engage and to motivate people to achieve goals. Its use is becoming very popular in software development organizations due to work being based upon human-centric and brain-intensive activity. This paper presents the topics of collaboration and gamification in the context of software engineering, and proposes a framework that identifies the most common collaboration issues that affect software development teams, and how to apply game elements to motivate a change on their behaviors.
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
A Method And System For Sentiment Classification And Emotion Classification [Us Patent 20170308523a1], Zhaoxia Wang, Rick Siow Mong Goh, Yinping Yang
Research Collection School Of Computing and Information Systems
A system and a method for classifying text messages, such as social media messages into sentiment valence categories are provided. The system comprising a module for decomposing text messages, a module for cleaning text messages, a module for producing feature data of text messages, and a module for classifying text messages into sentiment valence categories. The module for decomposing text messages is configured to: receive a text message, parse the text message into separate portions in response to parsing criteria based on sentence delimiters, wherein the separate portions are sentences, phrases and words, and rejoin at least some of the …
Human Action Recognition In Unconstrained Videos By Explicit Motion Modeling, Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, Chong-Wah Ngo
Human Action Recognition In Unconstrained Videos By Explicit Motion Modeling, Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Human action recognition in unconstrained videos is a challenging problem with many applications. Most state-of-the-art approaches adopted the well-known bag-of-features representations, generated based on isolated local patches or patch trajectories, where motion patterns, such as object-object and object-background relationships are mostly discarded. In this paper, we propose a simple representation aiming at modeling these motion relationships. We adopt global and local reference points to explicitly characterize motion information, so that the final representation is more robust to camera movements, which widely exist in unconstrained videos. Our approach operates on the top of visual codewords generated on dense local patch trajectories, …
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Event Detection In Wireless Sensor Networks In Random Spatial Sensors Deployments, Pengfei Zhang, Ido Nevat, Gareth W. Peters, Gaoxi Xiao, Hwee-Pink Tan
Event Detection In Wireless Sensor Networks In Random Spatial Sensors Deployments, Pengfei Zhang, Ido Nevat, Gareth W. Peters, Gaoxi Xiao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
We develop a new class of event detection algorithms in Wireless Sensor Networks where the sensors are randomly deployed spatially. We formulate the detection problem as a binary hypothesis testing problem and design the optimal decision rules for two scenarios, namely the Poisson Point Process and Binomial Point Process random deployments. To calculate the intractable marginal likelihood density, we develop three types of series expansion methods which are based on an Askey-orthogonal polynomials. In addition, we develop a novel framework to provide guidance on which series expansion is most suitable (i.e., most accurate) to use for different system parameters. Extensive …
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Assessing Developer Contribution With Repository Mining-Based Metrics, Jalerson Lima, Christoph Treude, Fernando Figueira Filho, Uirá Kulesza
Research Collection School Of Computing and Information Systems
Productivity as a result of individual developers' contributions is an important aspect for software companies to maintain their competitiveness in the market. However, there is no consensus in the literature on how to measure productivity or developer contribution. While some repository mining-based metrics have been proposed, they lack validation in terms of their applicability and usefulness from the individuals who will use them to assess developer contribution: team and project leaders. In this paper, we propose the design of a suite of metrics for the assessment of developer contribution, based on empirical evidence obtained from project and team leaders. In …
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Face Recognition On Large-Scale Video In The Wild With Hybrid Euclidean-And-Riemannian Metric Learning, Zhiwu Huang, R. Wang, S. Shan, X Chen
Research Collection School Of Computing and Information Systems
Face recognition on large-scale video in the wild is becoming increasingly important due to the ubiquity of video data captured by surveillance cameras, handheld devices, Internet uploads, and other sources. By treating each video as one image set, set-based methods recently have made great success in the field of video-based face recognition. In the wild world, videos often contain extremely complex data variations and thus pose a big challenge of set modeling for set-based methods. In this paper, we propose a novel Hybrid Euclidean-and-Riemannian Metric Learning (HERML) method to fuse multiple statistics of image set. Specifically, we represent each image …
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites, Jing Ma, Wei Gao, Zhongyu Wei, Yueming Lu, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Automatically identifying rumors from online social media especially microblogging websites is an important research issue. Most of existing work for rumor detection focuses on modeling features related to microblog contents, users and propagation patterns, but ignore the importance of the variation of these social context features during the message propagation over time. In this study, we propose a novel approach to capture the temporal characteristics of these features based on the time series of rumor's lifecycle, for which time series modeling technique is applied to incorporate various social context information. Our experiments using the events in two microblog datasets confirm …
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Choosing Your Weapons: On Sentiment Analysis Tools For Software Engineering Research, Robbert Jongeling, Subhajit Datta, Alexander Serebrenik
Research Collection School Of Computing and Information Systems
Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact …
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Constrained Feature Selection For Localizing Faults, Tien-Duy B. Le, David Lo, Ming Li
Research Collection School Of Computing and Information Systems
Developers often take much time and effort to find buggy program elements. To help developers debug, many past studies have proposed spectrum-based fault localization techniques. These techniques compare and contrast correct and faulty execution traces and highlight suspicious program elements. In this work, we propose constrained feature selection algorithms that we use to localize faults. Feature selection algorithms are commonly used to identify important features that are helpful for a classification task. By mapping an execution trace to a classification instance and a program element to a feature, we can transform fault localization to the feature selection problem. Unfortunately, existing …
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Research Collection School Of Computing and Information Systems
Mood has been systematically studied by psychologists for over 100 years. As mood is a subjective feeling, any study of mood must take into account and accurately capture user’s perception of an experienced feeling. In last 40 years, a number of pen-andpaper mood self-assessment scales have been proposed. Typically, a person is asked to separately rate various dimensions of the experienced feeling (e.g., pleasure and arousal) or mood items (interested, agitated, excited, etc.) on numeric scales (e.g., between 0 and 10). These partial ratings are then combined into an overall mood rating (or into its positive and negative affect). Penand-paper …
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Learning Relative Similarity From Data Streams: Active Online Learning Approaches, Shuji Hao, Peilin Zhao, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Relative similarity learning, as an important learning scheme for information retrieval, aims to learn a bi-linear similarity function from a collection of labeled instance-pairs, and the learned function would assign a high similarity value for a similar instance-pair and a low value for a dissimilar pair. Existing algorithms usually assume the labels of all the pairs in data streams are always made available for learning. However, this is not always realistic in practice since the number of possible pairs is quadratic to the number of instances in the database, and manually labeling the pairs could be very costly and time …