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Articles 6301 - 6330 of 9024
Full-Text Articles in Computer Sciences
Gpu Accelerated Counterexample Generation In Ltl Model Checking, Zhimin Wu, Yang Liu, Yun Liang, Jun Sun
Gpu Accelerated Counterexample Generation In Ltl Model Checking, Zhimin Wu, Yang Liu, Yun Liang, Jun Sun
Research Collection School Of Computing and Information Systems
Strongly Connected Component (SCC) based searching is one of the most popular LTL model checking algorithms. When the SCCs are huge, the counterexample generation process can be time-consuming, especially when dealing with fairness assumptions. In this work, we propose a GPU accelerated counterexample generation algorithm, which improves the performance by parallelizing the Breadth First Search (BFS) used in the counterexample generation. BFS work is irregular, which means it is hard to allocate resources and may suffer from imbalanced load. We make use of the features of latest CUDA Compute Architecture-NVIDIA Kepler GK110 to achieve the dynamic parallelism and memory hierarchy …
A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun
A Hybrid Model Of Connectors In Cyber-Physical Systems, Xiaohong Chen, Jun Sun, Meng Sun Sun
Research Collection School Of Computing and Information Systems
Compositional coordination models and languages play an important role in cyber-physical systems (CPSs). In this paper, we introduce a formal model for describing hybrid behaviors of connectors in CPSs. We extend the constraint automata model, which is used as the semantic model for the exogenous channel-based coordination language Reo, to capture the dynamic behavior of connectors in CPSs where the discrete and continuous dynamics co-exist and interact with each other. In addition to the formalism, we also provide a theoretical compositional approach for constructing the product automata for a Reo circuit, which is typically obtained by composing several primitive connectors …
Scc-Based Improved Reachability Analysis For Markov Decision Processes, Lin Gui, Jun Sun, Songzheng Song, Yang Liu, Jin Song Dong
Scc-Based Improved Reachability Analysis For Markov Decision Processes, Lin Gui, Jun Sun, Songzheng Song, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Markov decision processes (MDPs) are extensively used to model systems with both probabilistic and nondeterministic behavior. The problem of calculating the probability of reaching certain system states (hereafter reachability analysis) is central to the MDP-based system analysis. It is known that existing approaches on reachability analysis for MDPs are often inefficient when a given MDP contains a large number of states and loops, especially with the existence of multiple probability distributions. In this work, we propose a method to eliminate strongly connected components (SCCs) in an MDP using a divide-and-conquer algorithm, and actively remove redundant probability distributions in the MDP …
Practical Analysis Framework For Software-Based Attestation Scheme, Li Li, Hong Hu, Jun Sun, Yang Liu, Dong Jin Song
Practical Analysis Framework For Software-Based Attestation Scheme, Li Li, Hong Hu, Jun Sun, Yang Liu, Dong Jin Song
Research Collection School Of Computing and Information Systems
An increasing number of ”smart” embedded devices are employed in our living environment nowadays. Unlike traditional computer systems, these devices are often physically accessible to the attackers. It is therefore almost impossible to guarantee that they are un-compromised, i.e., that indeed the devices are executing the intended software. In such a context, software-based attestation is deemed as a promising solution to validate their software integrity. It guarantees that the software running on the embedded devices are un-compromised without any hardware support. However, designing software-based attestation protocols are shown to be error-prone. In this work, we develop a framework for design …
Tauth: Verifying Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Tauth: Verifying Timed Security Protocols, Li Li, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Quantitative timing is often relevant to the security of systems, like web applications, cyber-physical systems, etc. Verifying timed security protocols is however challenging as both arbitrary attacking behaviors and quantitative timing may lead to undecidability. In this work, we develop a service framework to support intuitive modeling of the timed protocol, as well as automatic verification with an unbounded number of sessions. The partial soundness and completeness of our verification algorithms are formally defined and proved. We implement our method into a tool called TAuth and the experiment results show that our approach is efficient and effective in both finding …
Learning Directional Co-Occurrence For Human Action Classification, Hong Liu, Mengyuan Liu, Qianru Sun
Learning Directional Co-Occurrence For Human Action Classification, Hong Liu, Mengyuan Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Spatio-temporal interest point (STIP) based methods have shown promising results for human action classification. However, state-of-art works typically utilize bag-of-visual words (BoVW), which focuses on the statistical distribution of features but ignores their inherent structural relationships. To solve this problem, a descriptor, namely directional pair-wise feature (DPF), is proposed to encode the mutual direction information between pairwise words, aiming at adding more spatial discriminant to BoVW. Firstly, STIP features are extracted and classified into a set of labeled words. Then in each frame, the DPF is constructed for every pair of words with different labels, according to their assigned directional …
Lifi: Line-Of-Sight Identification With Wifi, Zimu Zhou, Zheng Yang, Chenshu Wu, Wei Sun, Yunhao Liu
Lifi: Line-Of-Sight Identification With Wifi, Zimu Zhou, Zheng Yang, Chenshu Wu, Wei Sun, Yunhao Liu
Research Collection School Of Computing and Information Systems
Wireless LANs, especially WiFi, have been pervasively deployed and have fostered myriad wireless communication services and ubiquitous computing applications. A primary concern in designing each scenario-tailored application is to combat harsh indoor propagation environments, particularly Non-LineOf-Sight (NLOS) propagation. The ability to distinguish LineOf-Sight (LOS) path from NLOS paths acts as a key enabler for adaptive communication, cognitive radios, robust localization, etc. Enabling such capability on commodity WiFi infrastructure, however, is prohibitive due to the coarse multipath resolution with mere MAC layer RSSI. In this work, we dive into the PHY layer and strive to eliminate irrelevant noise and NLOS paths …
The Case For Open Source Software, Singapore Management University
The Case For Open Source Software, Singapore Management University
Perspectives@SMU
You use it more often than you are aware, and you can even use it to get a job
A Quantitative Analysis Of Decision Process In Social Groups Using Human Trajectories, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau, Ramayya Krishnan
A Quantitative Analysis Of Decision Process In Social Groups Using Human Trajectories, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
A group's collective action is an outcome of the group's decision-making process, which may be reached by either averaging of the individual preferences or following the choices of certain members in the group. Our problem here is to decide which decision process the group has adopted given the data of the collective actions. We propose a generic statistical framework to infer the group's decision process from the spatio-temporal data of group trajectories, where each "trajectory" is a sequence of group actions. This is achieved by systematically comparing each agent type's influence on the group actions based on an array of …
Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang
Haptics In Remote Collaborative Exercise Systems For Seniors, Hesam Alizadeh, Richard Tang, Ehud Sharlin, Anthony Tang
Research Collection School Of Computing and Information Systems
Group exercise provides motivation to follow and maintain a healthy daily exercise schedule while enjoying beneficial encouragement and social support from friends and exercise partners. However, mobility and transportation issues frequently prevent seniors from engaging in group activities. To address this problem, we investigated the exercise needs of seniors and developed a prototype remote exercise system. Our system uses haptic feedback to simulate assistive pushing and pulling of limbs when exercising with a partner. We developed three distinct vibration metaphors -- constant push/pull, corrective feedback, and notification -- to convey engagement and connection between exercise partners. We conducted a preliminary …
Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang
Detecting Anomaly Collections Using Extreme Feature Ranks, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Detecting anomaly collections is an important task with many applications, including spam and fraud detection. In an anomaly collection, entities often operate in collusion and hold different agendas to normal entities. As a result, they usually manifest collective extreme traits, i.e., members of an anomaly collection are consistently clustered toward the top or bottom ranks on certain features. We therefore propose to detect these anomaly collections by extreme feature ranks. We introduce a novel anomaly definition called Extreme Rank Anomalous Collection or ERAC. We propose a new measure of anomalousness capturing collective extreme traits based on a statistical model. As …
An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
Research Collection School Of Computing and Information Systems
Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components — users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user …
Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao
Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao
Research Collection School Of Computing and Information Systems
No abstract provided.
Technique For Authenticating H.264/Svc And Its Performance Evaluation Over Wireless Mobile Networks, Yifan Zhao, Swee Won Lo, Robert H. Deng, Xuhua Ding
Technique For Authenticating H.264/Svc And Its Performance Evaluation Over Wireless Mobile Networks, Yifan Zhao, Swee Won Lo, Robert H. Deng, Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, a bit stream-based authentication scheme for H.264/Scalable Video Coding (SVC) is proposed. The proposed scheme seamlessly integrates cryptographic algorithms and Erasure Correction Codes (ECCs) to SVC video streams such that the authenti- cated streams are format compliant with the SVC specifications and preserve the three- dimensional scalability (i.e., spatial, quality and temporal) of the original streams. We implement our scheme on a smart phone and study its performance over a realistic bursty packet-lossy wireless mobile network. Our analysis and experimental results show that the scheme achieves very high verification rates with lower communication overhead and much smaller …
Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein
Decentralized Multi-Agent Reinforcement Learning In Average-Reward Dynamic Dcops, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Researchers have introduced the Dynamic Distributed Constraint Optimization Problem (Dynamic DCOP) formulation to model dynamically changing multi-agent coordination problems, where a dynamic DCOP is a sequence of (static canonical) DCOPs, each partially different from the DCOP preceding it. Existing work typically assumes that the problem in each time step is decoupled from the problems in other time steps, which might not hold in some applications. Therefore, in this paper, we make the following contributions: (i) We introduce a new model, called Markovian Dynamic DCOPs (MD-DCOPs), where the DCOP in the next time step is a function of the value assignments …
Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau
Mechanisms For Arranging Ride Sharing And Fare Splitting For Last-Mile Travel Demands, Shih-Fen Cheng, Duc Thien Nguyen, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
A great challenge of city planners is to provide efficient and effective connection service to travelers using public transportation system. This is commonly known as the last-mile problem and is critical in promoting the utilization of public transportation system. In this paper, we address the last-mile problem by considering a dynamic and demand-responsive mechanism for arranging ride sharing on a non-dedicated commercial fleet (such as taxis or passenger vans). Our approach has the benefits of being dynamic, flexible, and with low setup cost. A critical issue in such ride-sharing service is how riders should be grouped and serviced, and how …
How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder
How Many Eyeballs Does A Bug Need? An Empirical Validation Of Linus' Law, Subhajit Datta, Proshanta Sarkar, Sutirtha Das, Sonu Sreshtha, Prasanth Lade, Subhashis Majumder
Research Collection School Of Computing and Information Systems
Linus’ Law reflects on a key characteristic of open source software development: developers’ tendency to closely work together in the bug resolution process. In this paper we empirically examine Linus’ Law using a data-set of 1,000+ Android bugs, owned by 70+ developers. Our results indicate that encouraging developers to work closely with one another has nuanced implications; while one form of contact may help reduce bug resolution time, another form can have quite the opposite effect. We present statistically significant evidence in support of our results and discuss their relevance at the individual and organizational levels.
Towards Semantically Secure Outsourcing Of Association Rule Mining On Categorical Data, Junzuo Lai, Yingjiu Li, Robert H. Deng, Jian Weng, Chaowen Guan, Qiang Yan
Towards Semantically Secure Outsourcing Of Association Rule Mining On Categorical Data, Junzuo Lai, Yingjiu Li, Robert H. Deng, Jian Weng, Chaowen Guan, Qiang Yan
Research Collection School Of Computing and Information Systems
When outsourcing association rule mining to cloud, it is critical for data owners to protect both sensitive raw data and valuable mining results from being snooped at cloud servers. Previous solutions addressing this concern add random noise to the raw data and/or encrypt the raw data with a substitution mapping. However, these solutions do not provide semantic security; partial information about raw data or mining results can be potentially discovered by an adversary at cloud servers under a reasonable assumption that the adversary knows some plaintext–ciphertext pairs. In this paper, we propose the first semantically secure solution for outsourcing association …
Identity-Based Encryption Secure Against Selective Opening Chosen-Ciphertext Attack, Junzuo Lai, Robert H. Deng, Shengli Liu, Jian Weng, Yunlei Zhao
Identity-Based Encryption Secure Against Selective Opening Chosen-Ciphertext Attack, Junzuo Lai, Robert H. Deng, Shengli Liu, Jian Weng, Yunlei Zhao
Research Collection School Of Computing and Information Systems
Security against selective opening attack (SOA) requires that in a multi-user setting, even if an adversary has access to all ciphertexts from users, and adaptively corrupts some fraction of the users by exposing not only their messages but also the random coins, the remaining unopened messages retain their privacy. Recently, Bellare, Waters and Yilek considered SOA-security in the identity-based setting, and presented the first identity-based encryption (IBE) schemes that are proven secure against selective opening chosen plaintext attack (SO-CPA). However, how to achieve SO-CCA security for IBE is still open. In this paper, we introduce a new primitive called extractable …
Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan
Handling Location Uncertainty In Event Driven Experimentation, Kartik Muralidharan, Srinivasan Seshan, Narayan Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
The wide spread use of smart phones has ushered in a wave of context-based advertising services that operate on pre-defined user events. A prime example is Location Based Advertising. What is missing though, is the ability to experiment with these services under varying event conditions with real users using their regular phones in real-world environments. Such experiments provide greater insight into user needs for and responsiveness towards context-based advertising applications. However, these event-driven experiments rely on data that arrive from sources such as mobile sensors which have inherent uncertainties associated with them. This effects the interpretation of the outcome of …
Didn’T You See My Message?: Predicting Attentiveness To Mobile Instant Messages, Martin Pielot, Rodrigo De Oliveira, Haewoon Kwak, Nuria. Oliver
Didn’T You See My Message?: Predicting Attentiveness To Mobile Instant Messages, Martin Pielot, Rodrigo De Oliveira, Haewoon Kwak, Nuria. Oliver
Research Collection School Of Computing and Information Systems
Mobile instant messaging (e.g., via SMS or WhatsApp) often goes along with an expectation of high attentiveness, i.e., that the receiver will notice and read the message within a few minutes. Hence, existing instant messaging services for mobile phones share indicators of availability, such as the last time the user has been online. However, in this paper we not only provide evidence that these cues create social pressure, but that they are also weak predictors of attentiveness. As remedy, we propose to share a machine-computed prediction of whether the user will view a message within the next few minutes or …
On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan
On Coordinating Pervasive Persuasive Agents, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
There is a growing interest in applying multiagent systems for smart-home environment supporting self-caring elderly. In this paper we investigate situations and conditions for coordination for such kind of system. We specify a high level architecture of it based on the notions of beliefs, desires, and intentions for both individual and group behavior of the agents including the human occupant's. The framework enables flexible coordinations among loosely-coupled heterogeneous agents that converse with the user. This work is conducted towards producing a coordination framework for agents and people in such a kind of smart-home environment as mentioned.
Physio@Home: Design Explorations To Support Movement Guidance, Richard Tang, Hesam Alizadeh, Anthony Tang, Scott Bateman, Joaquim A.P. Jorge
Physio@Home: Design Explorations To Support Movement Guidance, Richard Tang, Hesam Alizadeh, Anthony Tang, Scott Bateman, Joaquim A.P. Jorge
Research Collection School Of Computing and Information Systems
Patients typically undergo physiotherapy with the help of a physiotherapist who teaches, guides, and corrects the patients as they perform exercises. It would be nice if people could repeat these exercises at home, potentially improving their recovery rate. However, without guidance and/or corrective feedback from a physiotherapist, the patient will not know whether they are doing their exercises correctly. To address this problem, we implemented a prototype that guides patients through pre-recorded exercise movements using visual guides overlaid atop a mirror-view of the patient on a wall-mounted display. We conducted informal evaluations and pilot studies to assess our prototype and …
Medical Imaging Specialists And 3d: A Domain Perspective On Mobile 3d Interactions, Teddy Seyed, Frank Maurer, Francisco Marinho Rodrigues, Anthony Tang
Medical Imaging Specialists And 3d: A Domain Perspective On Mobile 3d Interactions, Teddy Seyed, Frank Maurer, Francisco Marinho Rodrigues, Anthony Tang
Research Collection School Of Computing and Information Systems
3D volumetric medical images, such as MRIs, are commonly explored and interacted with by medical imaging experts using systems that require keyboard and mouse-based techniques. These techniques have presented challenges for medical imaging specialists: 3D spatial navigation is difficult, in addition to the detailed selection and analysis of 3D medical images being difficult due to depth perception and occlusion issues. In this work, we explore a potential solution to these challenges by using tangible interaction techniques with a mobile device to simplify 3D interactions for medical imaging specialists. We discuss preliminary observations from our design sessions with medical imaging specialists …
One Space: Shared Visual Scenes For Active Free Play, Maayan Cohen, Kody Dillman, Haley Macleod, Seth Hunter, Anthony Tang
One Space: Shared Visual Scenes For Active Free Play, Maayan Cohen, Kody Dillman, Haley Macleod, Seth Hunter, Anthony Tang
Research Collection School Of Computing and Information Systems
Children engage in free play for emotional, physical and social development; researchers have explored supporting free play between physically remote playmates using videoconferencing tools. We show that the configuration of the video conferencing setup affects play. Specifically, we show that a shared visual scene configuration promotes fundamentally active forms of engaged, co-operative play.
Supporting Non-Verbal Visual Communication In Online Group Art Therapy, Brennan Jones, Kate Collie, Sara Prins Hankinson, Anthony Tang
Supporting Non-Verbal Visual Communication In Online Group Art Therapy, Brennan Jones, Kate Collie, Sara Prins Hankinson, Anthony Tang
Research Collection School Of Computing and Information Systems
Art therapy provides therapeutic benefit to people suffering from chronic pain, and recent work has explored supporting art therapy through online tools such as chat forums and discussion boards. These tools give people the benefit of engaging in art therapy without the burden of having to leave one’s home (when transportation may be a challenge), and allowing people to reveal their identities through dialogue and activity rather than through one’s appearance. However, these tools also do not provide much opportunity for collaboration and shared art making. Because group members are not aware of each other’s actions and non-verbal cues in …
Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin
Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin
Research Collection School Of Computing and Information Systems
It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge …
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni
Research Collection School Of Computing and Information Systems
Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Persistent Community Detection In Dynamic Social Networks, Siyuan Liu, Shuhui Wang, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
While community detection is an active area of research in social network analysis, little effort has been devoted to community detection using time-evolving social network data. We propose an algorithm, Persistent Community Detection (PCD), to identify those communities that exhibit persistent behavior over time, for usage in such settings. Our motivation is to distinguish between steady-state network activity, and impermanent behavior such as cascades caused by a noteworthy event. The results of extensive empirical experiments on real-life big social networks data show that our algorithm performs much better than a set of baseline methods, including two alternative models and the …
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Visual Analysis Of Uncertainty In Trajectories, Lu Lu, Nan Cao, Siyuan Liu, Lionel Ni, Xiaoru Yuan, Huamin Qu
Research Collection School Of Computing and Information Systems
Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. …