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Articles 5041 - 5070 of 9025
Full-Text Articles in Computer Sciences
Sparsity Based Reflection Removal Using External Patch Search, Renjie Wan, Boxin Shi, Ah-Hwee Tan, Alex C. Kot
Sparsity Based Reflection Removal Using External Patch Search, Renjie Wan, Boxin Shi, Ah-Hwee Tan, Alex C. Kot
Research Collection School Of Computing and Information Systems
Reflection removal aims at separating the mixture of the desired background scenes and the undesired reflections, when the photos are taken through the glass. It has both aesthetic and practical applications which can largely improve the performance of many multimedia tasks. Existing reflection removal approaches heavily rely on scene priors such as separable sparse gradients brought by different levels of blur, and they easily fail when such priors are not observed in many real scenes. Sparse representation models and nonlocal image priors have shown their effectiveness in image restoration with self similarity. In this work, we propose a reflection removal …
A Review On Neuropsychophysiological Correlates Of Flow, Fiona Fui-Hoon Nah, Tejaswini Yelamanchili, Keng Siau
A Review On Neuropsychophysiological Correlates Of Flow, Fiona Fui-Hoon Nah, Tejaswini Yelamanchili, Keng Siau
Research Collection School Of Computing and Information Systems
Games are captivating from a human-computer interaction point of view. They can induce an intensely involving and engaging experience termed flow, which refers to the optimal state of experience when one is fully immersed in an activity. This paper provides a review of the neural and psychophysiological correlates of flow as well as some directions for future research.
Effect Of Timing And Source Of Online Product Recommendations: An Eye-Tracking Study, Yan Shi, Qing Zeng, Fiona Fui-Hoon Nah, Chuan-Hoo Tan, Choon Ling Sia, Keng Siau, Jiaqi Yan
Effect Of Timing And Source Of Online Product Recommendations: An Eye-Tracking Study, Yan Shi, Qing Zeng, Fiona Fui-Hoon Nah, Chuan-Hoo Tan, Choon Ling Sia, Keng Siau, Jiaqi Yan
Research Collection School Of Computing and Information Systems
Online retail business has become an emerging market for almost all business owners. Online recommender systems provide better service to consumers during their decision making processes. In this study, a controlled lab experiment was conducted to assess the effect of recommendation timing (early, mid, and late) and recommendation source (expert reviews vs. consumer reviews) on online consumers’ interest and attention. Eye-tracking data was extracted from the experiment and analyzed. The results suggest that consumers show more interest in recommendation based on consumer reviews than expert reviews. Earlier recommendations do not receive greater attention than later recommendations.
A Nash Equilibrium Formulation Of A Tradable Credits Scheme For Incentivizing Transport Choices: From Next-Generation Public Transport Mode Choice To Hot Lanes, Salem Lahlou, Laura Wynter
A Nash Equilibrium Formulation Of A Tradable Credits Scheme For Incentivizing Transport Choices: From Next-Generation Public Transport Mode Choice To Hot Lanes, Salem Lahlou, Laura Wynter
Research Collection School Of Computing and Information Systems
We consider a tradable credits scheme for binary transport games where one option is faster (or more comfortable) than the other, but its quality of service suffers when usage is high. Applications can be found in mode choice (public transit versus road transport), premium (i.e., express bus) versus ordinary public transit, and fast (e.g., high-occupancy toll, or HOT) versus regular lanes on expressways. We are motivated in particular by the choice between public transport and use of the road network as a privilege to be discouraged. In a future where GPS-based time-distance-place road charging exists, such next-generation transport management strategies …
A Weighted Maximum Matching Algorithm For Influence Maximization And Structural Controllability, Giorgio Sartor, Yeow Khiang Chia, Laura Wynter, Justin Ruths
A Weighted Maximum Matching Algorithm For Influence Maximization And Structural Controllability, Giorgio Sartor, Yeow Khiang Chia, Laura Wynter, Justin Ruths
Research Collection School Of Computing and Information Systems
Structural control and influence maximization on networks both admit the problem of selecting a particular subset of nodes. In structural control, the subset of nodes should guarantee the controllability of the network (in the usual sense) for almost any combination of weights. In influence maximization, given a diffusion process over the network, the chosen subset of nodes (of a given cardinality) should produce the greatest diffusive influence over the rest of the network. While structural control exploits only the structure of the network, influence maximization depends both on the structure and the weights of the edges. We modify an algorithm …
Poster: Unobtrusive User Verification Using Piezoelectric Energy Harvesting, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Poster: Unobtrusive User Verification Using Piezoelectric Energy Harvesting, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
With the capability to harvest energy from low frequency motions or vibrations, piezoelectric energy harvesting has become a promising solution to achieve self-powered wearable system. Apart from generating energy to power the wearable devices, the output electricity signal of the PEH can also be used as an information source as it reflects the activity or motion patterns of the user. In this paper, we have designed and built an insole-based user authentication system by leveraging the AC voltage generated by the PEH during human walking. Meanwhile, the generated power is also collected and stored, which could be later used as …
Fusing Mobile, Wearable And Infrastructure Sensing For Immersive Daily Lifestyle Analytics, Sougata Sen
Fusing Mobile, Wearable And Infrastructure Sensing For Immersive Daily Lifestyle Analytics, Sougata Sen
Dissertations and Theses Collection
With the prevalence of sensors in public infrastructure as well as in personal devices, exploitation of data from these sensors to monitor and profile basic activities (e.g., locomotive states such as walking, and gestural actions such as smoking) has gained popularity. Basic activities identified by these sensors will drive the next generation of lifestyle monitoring applications and services. To provide more advanced and personalized services, these next-generation systems will need to capture and understand increasingly finer-grained details of various common daily life activities. In this dissertation, I demonstrate the possibility of building systems using offthe- shelf devices, that not only …
Recommending Personalized Schedules In Urban Environments, Cen Chen
Recommending Personalized Schedules In Urban Environments, Cen Chen
Dissertations and Theses Collection
In this thesis, we are broadly interested in solving real world problems that involve decision support for coordinating agent movements in dynamic urban environments, where people are agents exhibiting different human behavior patterns and preferences. The rapid development of mobile technologies makes it easier to capture agent behavioral and preference information. Such rich agent specific information, coupled with the explosive growth of computational power, opens many opportunities that we could potentially leverage, to better guide/influence the agents in urban environments. The purpose of this thesis is to investigate how we can effectively and efficiently guide and coordinate the agents with …
Efficient Large-Universe Multi-Authority Ciphertext-Policy Attribute-Based Encryption With White-Box Traceability, Kai Zhang, Hui Li, Jianfeng Ma, Ximeng Liu
Efficient Large-Universe Multi-Authority Ciphertext-Policy Attribute-Based Encryption With White-Box Traceability, Kai Zhang, Hui Li, Jianfeng Ma, Ximeng Liu
Research Collection School of Computing and Information Systems
Traceable multi-authority ciphertext-policy attribute-based encryption (CP-ABE) is a practical encryption method that can achieve user traceability and fine-grained access control simultaneously. However, existing traceable multi-authority CP-ABE schemes have two main limitations that prevent them from practical applications. First, these schemes only support small universe: the attributes must be fixed at system setup and the attribute space is restricted to polynomial size. Second, the schemes are either less expressive (the access policy is limited to “AND gates with wildcard”) or inefficient (the system is constructed in composite order bilinear groups). To address these limitations, we present a traceable large universe multi-authority …
On The Selection Of Anchors And Targets For Video Hyperlinking, Zhi-Qi Cheng, Hao Zhang, Xiao Wu, Chong-Wah Ngo
On The Selection Of Anchors And Targets For Video Hyperlinking, Zhi-Qi Cheng, Hao Zhang, Xiao Wu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
A problem not well understood in video hyperlinking is what qualifies a fragment as an anchor or target. Ideally, anchors provide good starting points for navigation, and targets supplement anchors with additional details while not distracting users with irrelevant, false and redundant information. The problem is not trivial for intertwining relationship between data characteristics and user expectation. Imagine that in a large dataset, there are clusters of fragments spreading over the feature space. The nature of each cluster can be described by its size (implying popularity) and structure (implying complexity). A principle way of hyperlinking can be carried out by …
Ubiear: Bringing Location-Independent Sound Awareness To The Hard-Of-Hearing People With Smartphones, Sicong Liu, Zimu Zhou, Junzhao Du, Longfei Shangguan, Jun Han, Xin Wang
Ubiear: Bringing Location-Independent Sound Awareness To The Hard-Of-Hearing People With Smartphones, Sicong Liu, Zimu Zhou, Junzhao Du, Longfei Shangguan, Jun Han, Xin Wang
Research Collection School Of Computing and Information Systems
Non-speech sound-awareness is important to improve the quality of life for the deaf and hard-of-hearing (DHH) people. DHH people, especially the young, are not always satisfied with their hearing aids. According to the interviews with 60 young hard-of-hearing students, a ubiquitous sound-awareness tool for emergency and social events that works in diverse environments is desired. In this paper, we design UbiEar, a smartphone-based acoustic event sensing and notification system. Core techniques in UbiEar are a light-weight deep convolution neural network to enable location-independent acoustic event recognition on commodity smartphons, and a set of mechanisms for prompt and energy-efficient acoustic sensing. …
Battery-Aware Mobile Data Service, Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, Kang G. Shin
Battery-Aware Mobile Data Service, Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, Kang G. Shin
Research Collection School Of Computing and Information Systems
Significant research has been devoted to reduce the energy consumption of mobile devices, but how to increase their energy supply has received far less attention. Moreover, reducing the energy consumption alone does not always extend the device operation time due to a unique battery property - the capacity it delivers hinges critically upon how it is discharged. In this paper, we propose B-MODS, a novel design of battery-aware mobile data service on mobile devices. B-MODS constructs battery-friendly discharge patterns utilizing the recovery effect so as to increase the capacity delivered from batteries while meeting data service requirements. We implement B-MODS …
Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson
Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson
Research Collection School Of Computing and Information Systems
No abstract provided.
Scalable Transfer Learning In Heterogeneous, Dynamic Environments, Trung Thanh Nguyen, Tomi Silander, Zhuoru Li, Tze-Yun Leong
Scalable Transfer Learning In Heterogeneous, Dynamic Environments, Trung Thanh Nguyen, Tomi Silander, Zhuoru Li, Tze-Yun Leong
Research Collection School Of Computing and Information Systems
Reinforcement learning is a plausible theoretical basis for developing self-learning, autonomous agents or robots that can effectively represent the world dynamics and efficiently learn the problem features to perform different tasks in different environments. The computational costs and complexities involved, however, are often prohibitive for real-world applications. This study introduces a scalable methodology to learn and transfer knowledge of the transition (and reward) models for model-based reinforcement learning in a complex world. We propose a variant formulation of Markov decision processes that supports efficient online-learning of the relevant problem features to approximate the world dynamics. We apply the new feature …
Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, Kai-Lung Hui, Seung Hyun Kim, Qiu-Hong Wang
Cybercrime Deterrence And International Legislation: Evidence From Distributed Denial Of Service Attacks, Kai-Lung Hui, Seung Hyun Kim, Qiu-Hong Wang
Research Collection School Of Computing and Information Systems
In this paper, we estimate the impact of enforcing the Convention on Cybercrime (COC) on deterring distributed denial of service (DDOS) attacks. Our data set comprises a sample of real, random spoof-source DDOS attacks recorded in 106 countries in 177 days in the period 2004-2008. We find that enforcing the COC decreases DDOS attacks by at least 11.8 percent, but a similar deterrence effect does not exist if the enforcing countries make a reservation on international cooperation. We also find evidence of network and displacement effects in COC enforcement. Our findings imply attackers in cyberspace are rational, motivated by economic …
Compress: A Comprehensive Framework Of Trajectory Compression In Road Networks, Yunheng Han, Weiwei Sun, Baihua Zheng
Compress: A Comprehensive Framework Of Trajectory Compression In Road Networks, Yunheng Han, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
More and more advanced technologies have become available to collect and integrate an unprecedented amount of data from multiple sources, including GPS trajectories about the traces of moving objects. Given the fact that GPS trajectories are vast in size while the information carried by the trajectories could be redundant, we focus on trajectory compression in this article. As a systematic solution, we propose a comprehensive framework, namely, COMPRESS (Comprehensive Paralleled Road-Network-Based Trajectory Compression), to compress GPS trajectory data in an urban road network. In the preprocessing step, COMPRESS decomposes trajectories into spatial paths and temporal sequences, with a thorough justification …
Sap: Improving Continuous Top-K Queries Over Streaming Data, Rui Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng, Guoren Wang
Sap: Improving Continuous Top-K Queries Over Streaming Data, Rui Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng, Guoren Wang
Research Collection School Of Computing and Information Systems
Continuous top-k query over streaming data is a fundamental problem in database. In this paper, we focus on the sliding window scenario, where a continuous top-k query returns the top-k objects within each query window on the data stream. Existing algorithms support this type of queries via incrementally maintaining a subset of objects in the window and try to retrieve the answer from this subset as much as possible whenever the window slides. However, since all the existing algorithms are sensitive to query parameters and data distribution, they all suffer from expensive incremental maintenance cost. In this paper, we propose …
Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The rapid emergence of head-mounted devices such as the Microsoft Holo-lens enables a wide variety of continuous vision applications. Such applications often adopt deep-learning algorithms such as CNN and RNN to extract rich contextual information from the first-person-view video streams. Despite the high accuracy, use of deep learning algorithms in mobile devices raises critical challenges, i.e., high processing latency and power consumption. In this paper, we propose DeepMon, a mobile deep learning inference system to run a variety of deep learning inferences purely on a mobile device in a fast and energy-efficient manner. For this, we designed a suite of …
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Deep learning has revolutionized vision sensing applications in terms of accuracy comparing to other techniques. Its breakthrough comes from the ability to extract complex high level features directly from sensor data. However, deep learning models are still yet to be natively supported on mobile devices due to high computational requirements. In this paper, we present DeepMon, a next generation of DeepSense [1] framework, to enable deep learning models on conventional mobile devices (e.g. Samsung Galaxy S7) for continuous vision sensing applications. Firstly, Deep-Mon exploits similarity between consecutive video frames for intermediate data caching within models to enhance inference latency. Secondly, …
Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee
Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee
Research Collection School Of Computing and Information Systems
It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor …
Cca Secure Encryption Supporting Authorized Equality Test On Ciphertexts In Standard Model And Its Applications, Yujue Wang, Hwee Hwa Pang, Ngoc Hieu Tran, Robert H. Deng
Cca Secure Encryption Supporting Authorized Equality Test On Ciphertexts In Standard Model And Its Applications, Yujue Wang, Hwee Hwa Pang, Ngoc Hieu Tran, Robert H. Deng
Research Collection School Of Computing and Information Systems
We present an encryption scheme for authorized equality test on ciphertexts (SEET), which allows the data owner to authorize a tester to compare her ciphertexts without decrypting their values. The security of SEET is formally proved against three types of adversary, two of them for ciphertext confidentiality in the phases before and after authorization respectively, and the third for token privacy. To the best of our knowledge, our SEET construction is the first encryption scheme supporting equality test on ciphertexts that is proven secure against the three types of adversary in the standard model. Our SEET construction outperforms existing schemes …
Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo
Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool-RACK-that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced …
Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai
Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai
Research Collection School Of Computing and Information Systems
Bugs severely hurt blockchain system dependability. A thorough understanding of blockchain bug characteristics is required to design effective tools for preventing, detecting and mitigating bugs. We perform an empirical study on bug characteristics in eight representative open source blockchain systems. First, we manually examine 1,108 bug reports to understand the nature of the reported bugs. Second, we leverage card sorting to label the bug reports, and obtain ten bug categories in blockchain systems. We further investigate the frequency distribution of bug categories across projects and programming languages. Finally, we study the relationship between bug categories and bug fixing time. The …
Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro
Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro
Research Collection School Of Computing and Information Systems
The Android packaging model offers ample opportunities for malware writers to piggyback malicious code in popular apps, which can then be easily spread to a large user base. Although recent research has produced approaches and tools to identify piggybacked apps, the literature lacks a comprehensive investigation into such phenomenon. We fill this gap by: 1) systematically building a large set of piggybacked and benign apps pairs, which we release to the community; 2) empirically studying the characteristics of malicious piggybacked apps in comparison with their benign counterparts; and 3) providing insights on piggybacking processes. Among several findings providing insights analysis …
An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo
An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most important activities during software development and maintenance. A substantial number of bugs are often fixed more than once due to incomplete initial fixes which need to be followed up by supplementary fixes. Automatically recommending relevant change locations for supplementary bug fixes can help developers to improve their productivity. It also help improve the reliability of systems by highlighting locations that a developer potentially needs to change to completely remove a bug. Unfortunately, a recent study by Park et al. shows that many change recommendation techniques do not work for supplementary bug fixes. In …
Cataloging Github Repositories, Abhishek Sharma, Ferdian Thung, Pavneet Singh Kochhar, Agus Sulistya, David Lo
Cataloging Github Repositories, Abhishek Sharma, Ferdian Thung, Pavneet Singh Kochhar, Agus Sulistya, David Lo
Research Collection School Of Computing and Information Systems
GitHub is one of the largest and most popular repository hosting service today, having about 14 million users and more than 54 million repositories as of March 2017. This makes it an excellent platform to find projects that developers are interested in exploring. GitHub showcases its most popular projects by cataloging them manually into categories such as DevOps tools, web application frameworks, and game engines. We propose that such cataloging should not be limited only to popular projects. We explore the possibility of developing such cataloging system by automatically extracting functionality descriptive text segments from readme files of GitHub repositories. …
Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
In this paper, we describe the progressive design of the gesture recognition module of an automated food journaling system - Annapurna. Annapurna runs on a smartwatch and utilises data from the inertial sensors to first identify eating gestures, and then captures food images which are presented to the user in the form of a food journal. We detail the lessons we learnt from multiple in-the-wild studies, and show how eating recognizer is refined to tackle challenges such as (i) high gestural diversity, and (ii) non-eating activities with similar gestural signatures. Annapurna is finally robust (identifying eating across a wide diversity …
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Research Collection School Of Computing and Information Systems
Assertions are often used to test the assumptions that developers have about a program. An assertion contains a boolean expression which developers believe to be true at a particular program point. It throws an error if the expression is not satisfied, which helps developers to detect and correct bugs. Since assertions make developer assumptions explicit, assertions are also believed to improve under-standability of code. Recently, Casalnuovo et al. analyse C and C++ programs to understand the relationship between assertion usage and defect occurrence. Their results show that asserts have a small effect on reducing the density of bugs and developers …
An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo
An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo
Research Collection School Of Computing and Information Systems
Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …
The Dark Side Of Banning Hacking Technique Discussion, Qiu-Hong Wang, Ting Zhang Le
The Dark Side Of Banning Hacking Technique Discussion, Qiu-Hong Wang, Ting Zhang Le
Research Collection School Of Computing and Information Systems
Prior studies have evidenced the effectiveness of more severe and broader enforcement in deterringcybercrimes. This study addresses the other side of the story. Our data analysis shows that theenforcement against the production / distribution / possession of computer misuse tools tends toincrease the contribution on detection and protection related posts in online hacker forums. Butthis enforcement may discourage those contributors who had originally actively contributed to theprotection discussions. Thus government regulations have to be cautiously justify the incentives ofmultiple parties in the cybersecurity context.