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History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
History Driven Program Repair, Xuan-Bach D. Le, David Lo, Claire Le Goues
Research Collection School Of Computing and Information Systems
Effective automated program repair techniques have great potential to reduce the costs of debugging and maintenance. Previously proposed automated program repair (APR) techniques often follow a generate-and-validate and test- case-driven procedure: They first randomly generate a large pool of fix candidates and then exhaustively validate the quality of the candidates by testing them against existing or provided test suites. Unfortunately, many real-world bugs cannot be repaired by existing techniques even after more than 12 hours of computation in a multi-core cloud environment. More work is needed to advance the capabilities of modern APR techniques. We propose a new technique that …
Detection Of Bird Nests In Overhead Catenary System Images For High-Speed Rail, Xiao Wu, Ping Yuan, Qiang Peng, Chong-Wah Ngo, Jun-Yan He
Detection Of Bird Nests In Overhead Catenary System Images For High-Speed Rail, Xiao Wu, Ping Yuan, Qiang Peng, Chong-Wah Ngo, Jun-Yan He
Research Collection School Of Computing and Information Systems
The high-speed rail system provides a fast, reliable and comfortable means to transport large number of travelers over long distances. The existence of bird nests in overhead catenary system (OCS) can hazard to the safety of the high-speed rails, which will potentially result in long time delays and expensive damages. A vision-based intelligent inspection system capable of automatic detection of bird nests built on overhead catenary would avoid the damages and increase the reliability and punctuality, and therefore is attractive for a high-speed railway system. However, OCS images exhibit great variations with lighting changes, illumination conditions and complex backgrounds, which …
Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo
Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This article considers multimedia question answering beyond factoid and how-to questions. We are interested in searching videos for answering opinion-oriented questions that are controversial and hotly debated. Examples of questions include "Should Edward Snowden be pardoned?" and "Obamacare-unconstitutional or not?". These questions often invoke emotional response, either positively or negatively, hence are likely to be better answered by videos than texts, due to the vivid display of emotional signals visible through facial expression and speaking tone. Nevertheless, a potential answer of duration 60s may be embedded in a video of 10min, resulting in degraded user experience compared to reading the …
Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang
Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang
Research Collection School Of Computing and Information Systems
The fault detection of electrical or mechanical anomalies in induction motors has been a challenging problem for researchers over decades to ensure the safety and economic operations of industrial processes. To address this issue, this paper studies the stator current data obtained from inverter-fed laboratory induction motors and investigates the unique signatures of the healthy and faulty motors with the aim of developing knowledge based fault detection method for performing online detection of motor fault problems, such as broken-rotor-bar and bearing faults. Stator current data collected from induction motors were analyzed by leveraging fast Fourier transform (FFT), and the FFT …
Harmonic Analysis In Integrated Energy System Based On Compressed Sensing, Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang
Harmonic Analysis In Integrated Energy System Based On Compressed Sensing, Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In …
Human Activity Prediction By Mapping Grouplets To Recurrent Self-Organizing Map, Qianru Sun, Hong Liu, Mengyuan Liu, Tianwei Zhang
Human Activity Prediction By Mapping Grouplets To Recurrent Self-Organizing Map, Qianru Sun, Hong Liu, Mengyuan Liu, Tianwei Zhang
Research Collection School Of Computing and Information Systems
Human activity prediction is defined as inferring the high-level activity category with the observation of only a few action units. It is very meaningful for time-critical applications such as emergency surveillance. For efficient prediction, we represent the ongoing human activity by using body part movements and taking full advantage of inherent sequentiality, then find the best matching activity template by a proper aligning measurement.In streaming videos, dense spatio-temporal interest points (STIPs) are first extracted as low-level descriptors for their high detection efficiency. Then, sparse grouplets, i.e., clustered point groups, are located to represent body part movements, for which we propose …
Campus-Scale Mobile Crowd-Tasking: Deployment & Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Campus-Scale Mobile Crowd-Tasking: Deployment & Behavioral Insights, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Nikita Jaiman, Randy Tandriansiyah, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta
Research Collection School Of Computing and Information Systems
Mobile crowd-tasking markets are growing at an unprecedented rate with increasing number of smartphone users. Such platforms differ from their online counterparts in that they demand physical mobility and can benefit from smartphone processors and sensors for verification purposes. Despite the importance of such mobile crowd-tasking markets, little is known about the labor supply dynamics and mobility patterns of the users. In this paper we design, develop and experiment with a realworld mobile crowd-tasking platform, called TA$Ker. Our contributions are two-fold: (a) We develop TA$Ker, a system that allows us to empirically study the worker responses to push vs. pull …
Capstone Course On Facilitating Business Brainstorming In A Global Workplace, Edison Jun Hao Lim, Benjamin Gan
Capstone Course On Facilitating Business Brainstorming In A Global Workplace, Edison Jun Hao Lim, Benjamin Gan
Research Collection School Of Computing and Information Systems
This paper describes our capstone team’s experience toward building a IT system for business brainstorming at work. The Canvas project aims to facilitate the Business Model Canvas exercise between employees at NEC Corporation. Traditional brainstorming meetings require employees to be in the same location, are hard to organize and are hard to archive. Our team, Rokoo, developed a web application that resolves these challenges by allowing global employees to brainstorm together on the same platform.
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Research Collection School Of Computing and Information Systems
No abstract provided.
Exploring Heterogeneous Features For Query-Focused Summarization Of Categorized Community Answers, Wei Wei, Zhaoyan Ming, Liqiang Nie, Guohui Li, Jianjun Li, Feida Zhu, Tianfeng Shang, Changyin Luo
Exploring Heterogeneous Features For Query-Focused Summarization Of Categorized Community Answers, Wei Wei, Zhaoyan Ming, Liqiang Nie, Guohui Li, Jianjun Li, Feida Zhu, Tianfeng Shang, Changyin Luo
Research Collection School Of Computing and Information Systems
Community-based question answering (cQA) is a popular type of online knowledge-sharing web service where users ask questions and obtain answers contributed by others. To enhance knowledge sharing, cQA also provides users with a retrieval function to access the historical question-answer pairs (QAs). However, it is still ineffective in that the retrieval result is typically a ranking list of potentially relevant QAs, rather than a succinct and informative answer. To alleviate the problem, this paper proposes a three-level scheme, which aims to generate a query-focused summary-style answer in terms of two factors, i.e., novelty and redundancy. Specifically, we first retrieve a …
Ambient And Smartphone Sensor Assisted Adl Recognition In Multi-Inhabitant Smart Environments, Nirmalya Roy, Archan Misra, Diane Cook
Ambient And Smartphone Sensor Assisted Adl Recognition In Multi-Inhabitant Smart Environments, Nirmalya Roy, Archan Misra, Diane Cook
Research Collection School Of Computing and Information Systems
Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users’ spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user …
Negative Factor: Improving Regular-Expression Matching In Strings, Xiaochun Yang, Tao Qiu, Bin Wang, Baihua Zheng, Yaoshu Wang, Chen Li
Negative Factor: Improving Regular-Expression Matching In Strings, Xiaochun Yang, Tao Qiu, Bin Wang, Baihua Zheng, Yaoshu Wang, Chen Li
Research Collection School Of Computing and Information Systems
The problem of finding matches of a regular expression (RE) on a string exists in many applications such as text editing, biosequence search, and shell commands. Existing techniques first identify candidates using substrings in the RE, then verify each of them using an automaton. These techniques become inefficient when there are many candidate occurrences that need to be verified. In this paper we propose a novel technique that prunes false negatives by utilizing negative factors, which are substrings that cannot appear in an answer. A main advantage of the technique is that it can be integrated with many existing algorithms …
Mobile App Tagging, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Mobile App Tagging, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
Mobile app tagging aims to assign a list of keywords indicating core functionalities, main contents, key features or concepts of a mobile app. Mobile app tags can be potentially useful for app ecosystem stakeholders or other parties to improve app search, browsing, categorization, and advertising, etc. However, most mainstream app markets, e.g., Google Play, Apple App Store, etc., currently do not explicitly support such tags for apps. To address this problem, we propose a novel auto mobile app tagging framework for annotating a given mobile app automatically, which is based on a search-based annotation paradigm powered by machine learning techniques. …
Ict-Travel: Mobile Public Transport Companion For The Visually Impaired, Linting Cui, Kenny Ngo, Benjamin Kok Siew Gan
Ict-Travel: Mobile Public Transport Companion For The Visually Impaired, Linting Cui, Kenny Ngo, Benjamin Kok Siew Gan
Research Collection School Of Computing and Information Systems
The smartphone application widespread adoption has brought about many conveniences to the general population. Unfortunately, like most technology adoption, the focus lacks behind for people with disabilities. Yet, the potential for IT to personalize the mobile application for these groups is high. In our capstone project at Singapore Management University, we developed an iOS application for the visually impaired to use the public transport in Singapore. Beyond meeting the initial requirements, we tested with the visually impaired in order to empathize and cater to their specific needs. This software engineering project is a lesson in iterative software development with changing …
A Proactive Sampling Approach To Project Scheduling Under Uncertainty, Pradeep Varakantham, Na Fu, Hoong Chuin Lau
A Proactive Sampling Approach To Project Scheduling Under Uncertainty, Pradeep Varakantham, Na Fu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Uncertainty in activity durations is a key characteristic of many real world scheduling problems in manufacturing, logistics and project management. RCPSP/max with durational uncertainty is a general model that can be used to represent durational uncertainty in a wide variety of scheduling problems where there exist resource constraints. However, computing schedules or execution strategies for RCPSP/max with durational uncertainty is NP-hard and hence we focus on providing approximation methods in this paper. We pro- vide a principled approximation approach based on Sample Average Approximation (SAA) to compute proactive schedules for RCPSP/max with durational uncertainty. We further contribute an extension to …
Achieving Stable And Fair Profit Allocation With Minimum Subsidy In Collaborative Logistics, Lucas Agussurja, Hoong Chuin Lau, Shih-Fen Cheng
Achieving Stable And Fair Profit Allocation With Minimum Subsidy In Collaborative Logistics, Lucas Agussurja, Hoong Chuin Lau, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
With the advent of e-commerce, logistics providers are faced with the challenge of handling fluctuating and sparsely distributed demand, which raises their operational costs significantly. As a result, horizontal cooperation are gaining momentum around the world. One of the major impediments, however, is the lack of stable and fair profit sharing mechanism. In this paper, we address this problem using the framework of computational cooperative games. We first present cooperative vehicle routing game as a model for collaborative logistics operations. Using the axioms of Shapley value as the conditions for fairness, we show that a stable, fair and budget balanced …
Online Learning Of Arima For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun
Online Learning Of Arima For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun
Research Collection School Of Computing and Information Systems
Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, which restricts its applications and makes it inefficient for handling large-scale real data. In this paper, we propose online learning algorithms for estimating ARIMA models under relaxed assumptions on the noise terms, which is suitable to a wider range of applications and enjoys high computational efficiency. The idea of our ARIMA method is to …
Online Cross-Modal Hashing For Web Image Retrieval, Liang Xie, Jialie Shen, Lei Zhu
Online Cross-Modal Hashing For Web Image Retrieval, Liang Xie, Jialie Shen, Lei Zhu
Research Collection School Of Computing and Information Systems
Cross-modal hashing (CMH) is an efficient technique for the fast retrieval of web image data, and it has gained a lot of attentions recently. However, traditional CMH methods usually apply batch learning for generating hash functions and codes. They are inefficient for the retrieval of web images which usually have streaming fashion. Online learning can be exploited for CMH. But existing online hashing methods still cannot solve two essential problems: Efficient updating of hash codes and analysis of cross-modal correlation. In this paper, we propose Online Cross-modal Hashing (OCMH) which can effectively address the above two problems by learning the …
Robust Decision Making For Stochastic Network Design, Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon
Robust Decision Making For Stochastic Network Design, Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon
Research Collection School Of Computing and Information Systems
We address the problem of robust decision making for stochastic network design. Our work is motivated by spatial conservation planning where the goal is to take management decisions within a fixed budget to maximize the expected spread of a population of species over a network of land parcels. Most previous work for this problem assumes that accurate estimates of different network parameters (edge activation probabilities, habitat suitability scores) are available, which is an unrealistic assumption. To address this shortcoming, we assume that network parameters are only partially known, specified via interval bounds. We then develop a decision making approach that …
Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham
Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Voice is a critical user interface on smart devices (wearables, phones, speakers, televisions) to access applications (or services) available on them. Unfortunately, only a few native applications (provided by the OS developer) are typically voice enabled in devices of today. Since, the utility of a smart device is determined more by the strength of external applications developed for the device, voice enabling non-native applications in a scalable, seamless manner within the device is a critical use case and is the focus of our work. We have developed a Natural Language Understanding (NLU) framework that uses templates supported by the application …
Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Online Spatio-Temporal Matching In Stochastic And Dynamic Domains, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Spatio-temporal matching of services to customers online is a problem that arises on a large scale in many domains associated with shared transportation (ex: taxis, ride sharing, super shuttles, etc.) and delivery services (ex: food, equipment, clothing, home fuel, etc.). A key characteristic of these problems is that matching of services to customers in one round has a direct impact on the matching of services to customers in the next round. For instance, in the case of taxis, in the second round taxis can only pick up customers closer to the drop off point of the customer from the first …
Multiagent Based Algorithmic Approach For Fast Response In Railway Disaster Handling, Poulami Dalapati, Arambam James Singh, Animesh Dutta
Multiagent Based Algorithmic Approach For Fast Response In Railway Disaster Handling, Poulami Dalapati, Arambam James Singh, Animesh Dutta
Research Collection School Of Computing and Information Systems
Disaster management in railway network is an important issue. It requires to minimize negative impact and also fast, efficient recovery from the disturbances. The main challenge here is that, the effect of inconvenience spreads out very fast in time and space. It takes noticeable amount of time to get back everything in the previous situation. This paper proposes a multi agent based algorithmic approach for disaster handling in Railway Network. This takes care of fast response to get total number of affected trains in a fast and efficient manner. We propose few algorithms to handle this situation and simulate it …
Multiagent-Based Route Guidance For Increasing The Chance Of Arrival On Time, Zhiguang Cao, Hongliang Guo, Jie Zhang, Ulrich Fastenrath
Multiagent-Based Route Guidance For Increasing The Chance Of Arrival On Time, Zhiguang Cao, Hongliang Guo, Jie Zhang, Ulrich Fastenrath
Research Collection School Of Computing and Information Systems
Transportation and mobility are central to sustainable urban development, where multiagent-based route guidance is widely applied. Traditional multiagent-based route guidance always seeks LET (least expected travel time) paths. However, drivers usually have specific expectations, i.e., tight or loose deadlines, which may not be all met by LET paths. We thus adopt and extend the probability tail model that aims to maximize the probability of reaching destinations before deadlines. Specifically, we propose a decentralized multiagent approach, where infrastructure agents locally collect intentions of concerned vehicle agents and formulate route guidance as a route assignment problem, to guarantee their arrival on time. …
Copyright Law And The Supply Of Creative Work: Evidence From The Movies, Ivan Paak Liang Png, Qiu-Hong Wang
Copyright Law And The Supply Of Creative Work: Evidence From The Movies, Ivan Paak Liang Png, Qiu-Hong Wang
Research Collection School Of Computing and Information Systems
There is almost no empirical evidence on the extent to whichcopyright law works in the sense of increasing the production of creative work.Here, we study the impact of two major changes in copyright law – the extensionof copyright term and the European Rental Directive – on the production ofmovies. In a panel of 23 OECD countries, among which 19 extendedcopyright term at various times between 1991–2005, we found no statisticallyrobust evidence that copyright term extension was associated with higher movie production.In a panel of 17 European countries between 1991–2005, wefound no statistically robust evidence that compliance with the RentalDirective was …
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
Even though social media offers plenty of business opportunities, for a company to identify the right audience from the massive amount of social media data is highly challenging given finite resources and marketing budgets. In this paper, we present a ranking mechanism that is capable of identifying the top-k social audience members on Twitter based on an index. Data from three different Twitter business account owners were used in our experiments to validate this ranking mechanism. The results show that the index developed using a combination of semi-supervised and supervised learning methods is indeed generic enough to retrieve relevant audience …
Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar
Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar
Research Collection School Of Computing and Information Systems
We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of …
Solving Risk-Sensitive Pomdps With And Without Cost Observations, Ping Hou, William Yeoh, Pradeep Varakantham
Solving Risk-Sensitive Pomdps With And Without Cost Observations, Ping Hou, William Yeoh, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Partially Observable Markov Decision Processes (POMDPs) are often used to model planning problems under uncertainty. The goal in Risk-Sensitive POMDPs (RS-POMDPs) is to find a policy that maximizes the probability that the cumulative cost is within some user-defined cost threshold. In this paper, unlike existing POMDP literature, we distinguish between the two cases of whether costs can or cannot be observed and show the empirical impact of cost observations. We also introduce a new search-based algorithm to solve RS-POMDPs and show that it is faster and more scalable than existing approaches in two synthetic domains and a taxi domain generated …
One Size Does Not Fit All: A Game-Theoretic Approach For Dynamically And Effectively Screening For Threats, Matthew Brown, Arunesh Sinha, Aaron Schlenker, Milind Tambe
One Size Does Not Fit All: A Game-Theoretic Approach For Dynamically And Effectively Screening For Threats, Matthew Brown, Arunesh Sinha, Aaron Schlenker, Milind Tambe
Research Collection School Of Computing and Information Systems
An effective way of preventing attacks in secure areas is to screen for threats (people, objects) before entry, e.g., screening of airport passengers. However, screening every entity at the same level may be both ineffective and undesirable. The challenge then is to find a dynamic approach for randomized screening, allowing for more effective use of limited screening resources, leading to improved security. We address this challenge with the following contributions: (1) a threat screening game (TSG) model for general screening domains; (2) an NP-hardness proof for computing the optimal strategy of TSGs; (3) a scheme for decomposing TSGs into subgames …
Efficient Collective Spatial Keyword Query Processing On Road Networks, Yunjun Gao, Jingwen Zhao, Baihua Zheng, Gang Chen
Efficient Collective Spatial Keyword Query Processing On Road Networks, Yunjun Gao, Jingwen Zhao, Baihua Zheng, Gang Chen
Research Collection School Of Computing and Information Systems
The collective spatial keyword query (CSKQ), an important variant of spatial keyword queries, aims to find a set of the objects that collectively cover users' queried keywords, and those objects are close to the query location and have small inter-object distances. Existing works only focus on the CSKQ problem in the Euclidean space, although we observe that, in many real-life applications, the closeness of two spatial objects is measured by their road network distance. Thus, existing methods cannot solve the problem of network-based CSKQ efficiently. In this paper, we study the problem of collective spatial keyword query processing on road …
Accurate Online Video Tagging Via Probabilistic Hybrid Modeling, Jialie Shen, Meng Wang, Tat-Seng Chua
Accurate Online Video Tagging Via Probabilistic Hybrid Modeling, Jialie Shen, Meng Wang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Accurate video tagging has been becoming increasingly crucial for online video management and search. This article documents a novel framework called comprehensive video tagger (CVTagger) to facilitate accurate tag-based video annotation. The system applies both multimodal and temporal properties combined with a novel classification framework with hierarchical structure based on multilayer concept model and regression analysis. The advanced architecture enables effective incorporation of both video concept dependency and temporal dynamics. Using a large-scale test collection containing 50,000 YouTube videos, a set of empirical studies have been carried out and experimental results demonstrate various advantages of CVTagger over the state-of-the-art techniques.