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Articles 6361 - 6390 of 8479
Full-Text Articles in Computer Sciences
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
An Empirical Study Of Bugs In Machine Learning Systems, Ferdian Thung, Shaowei Wang, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Many machine learning systems that include various data mining, information retrieval, and natural language processing code and libraries have being used in real world applications. Search engines, internet advertising systems, product recommendation systems are sample users of these algorithm intensive code and libraries. Machine learning code and toolkits have also been used in many recent studies on software mining and analytics that aim to automate various software engineering tasks. With the increasing number of important applications of machine learning systems, the reliability of such systems is also becoming increasingly important. A necessary step for ensuring reliability of such systems is …
Understanding Engagement In Educational Computer Games, Fiona Fui-Hoon Nah, Yunjie Zhou, Adeline Boey, Hanji Li
Understanding Engagement In Educational Computer Games, Fiona Fui-Hoon Nah, Yunjie Zhou, Adeline Boey, Hanji Li
Research Collection School Of Computing and Information Systems
This paper presents an empirical study to understand engagement in educational computer games. Engagement is defined as an experience that occupies an individual’s attention and captures one’s interest. The nature of engagement is viewed as comprising conditions, actions, and outcomes of engagement. The data collection method includes in-depth interviews with 12 educational computer game players who have experienced engagement in playing these games. We used the Grounded Theory (GT) approach to develop an understanding of user engagement in the computer game-based learning context.
Handling Interpretation And Representation In Multilingual Research: A Meta-Study Of Pragmatic Issues Resulting From The Use Of Multiple Languages In A Qualitative Information Systems Research Work, Ilse Baumgartner
Research Collection School Of Computing and Information Systems
Although the number of multilingual qualitative research studies appears to be growing, investigations concerned with methodological issues arising from the use of several languages within a single research are still very scarce. Most of these seem to deal exclusively with issues related to the use of interpreters and translators in qualitative research (e.g., Temple & Edwards, 2002; Temple, Edwards & Alexander, 2006; Edwards, 1998; Temple & Young 2004). Methodological investigations going beyond pure translation dilemmas in qualitative research are, however, almost non-existent. The reason for this seems to be simple: the situation where the researcher possesses mother-tongue fluency in all …
Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang
Automatic Defect Categorization, Ferdian Thung, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Defects are prevalent in software systems. In order to understand defects better, industry practitioners often categorize bugs into various types. One common kind of categorization is the IBM’s Orthogonal Defect Classification (ODC). ODC proposes various orthogonal classification of defects based on much information about the defects, such as the symptoms and semantics of the defects, the root cause analysis of the defects, and many more. With these category labels, developers can better perform post-mortem analysis to find out what the common characteristics of the defects that plague a particular software project are. Albeit the benefits of having these categories, for …
Oto: Online Trust Oracle For User-Centric Trust Establishment, Tiffany Hyun-Jin Kim, Payas Gupta, Jun Han, Emmanuel Owusu, Jason Hong, Adrian Perrig, Debin Gao
Oto: Online Trust Oracle For User-Centric Trust Establishment, Tiffany Hyun-Jin Kim, Payas Gupta, Jun Han, Emmanuel Owusu, Jason Hong, Adrian Perrig, Debin Gao
Research Collection School Of Computing and Information Systems
Malware continues to thrive on the Internet. Besides automated mechanisms for detecting malware, we provide users with trust evidence information to enable them to make informed trust decisions. To scope the problem, we study the challenge of assisting users with judging the trustworthiness of software downloaded from the Internet. Through expert elicitation, we deduce indicators for trust evidence, then analyze these indicators with respect to scalability and robustness. We design OTO, a system for communicating these trust evidence indicators to users, and we demonstrate through a user study the effectiveness of OTO, even with respect to IE’s SmartScreen Filter (SSF). …
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The Violent Scene Detection task offers a very practical challenge in detecting complex and diverse violent video clips in movies. In this working note paper, we will briefly describe our system and discuss the results, which achieved top performance in mAP@201 and runner-up in mAP@100, among all 35 submissions worldwide. The central component of our system is a set of features derived from the appearance and motion of local patch trajectories [2]. We use these features and SVM classifier as the baseline approach and add in a few other components to further improve the performance. Our findings indicate that the …
Trajectory-Based Modeling Of Human Actions With Motion Reference Points, Yu-Gang Jiang, Qi Dai, Xiangyang Xue, Wei Liu, Chong-Wah Ngo
Trajectory-Based Modeling Of Human Actions With Motion Reference Points, Yu-Gang Jiang, Qi Dai, Xiangyang Xue, Wei Liu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Human action recognition in videos is a challenging problem with wide applications. State-of-the-art approaches often adopt the popular bag-of-features representation based on isolated local patches or temporal patch trajectories, where motion patterns like object relationships are mostly discarded. This paper proposes a simple representation specifically aimed at the modeling of such motion relationships. We adopt global and local reference points to characterize motion information, so that the final representation can be robust to camera movement. Our approach operates on top of visual codewords derived from local patch trajectories, and therefore does not require accurate foreground-background separation, which is typically a …
A Flexible Mixed Integer Programming Framework For Nurse Scheduling, Murphy Choy, Michelle L. F. Cheong
A Flexible Mixed Integer Programming Framework For Nurse Scheduling, Murphy Choy, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
In this paper, a nurse-scheduling model is developed using mixed integer programming model. It is deployed to a general care ward to replace and automate the current manual approach for scheduling. The developed model differs from other similar studies in that it optimizes both hospitals requirement as well as nurse preferences by allowing flexibility in the transfer of nurses from different duties. The model also incorporated additional policies which are part of the hospitals requirement but not part of the legislations. Hospitals key primary mission is to ensure continuous ward care service with appropriate number of nursing staffs and the …
Self-Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Self-Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Model Checking Software Architecture Design, Jiexin Zhang, Yang Liu, Jing Sun, Jin Song Dong, Jun Sun
Model Checking Software Architecture Design, Jiexin Zhang, Yang Liu, Jing Sun, Jin Song Dong, Jun Sun
Research Collection School Of Computing and Information Systems
Software Architecture plays an essential role in the high level description of a system design. Despite its importance in the software engineering practice, the lack of formal description and verification support hinders the development of quality architectural models. In this paper, we present an automated approach to the modeling and verification of software architecture designs using the Process Analysis Toolkit (PAT). We present the formal syntax of the Wright# architecture description language together with its operational semantics in Labeled Transition System (LTS). A dedicated model checking module for Wright# is implemented in the PAT verification framework based on the proposed …
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
Neural Modeling Of Episodic Memory: Encoding, Retrieval, And Forgetting, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Janusz A. Starzyk
Research Collection School Of Computing and Information Systems
This paper presents a neural model that learns episodic traces in response to a continuous stream of sensory input and feedback received from the environment. The proposed model, based on fusion Adaptive Resonance Theory (fusion ART) network, extracts key events and encodes spatio-temporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs parallel search of stored episodic traces continuously. Combined with a mechanism of gradual forgetting, the model is able to achieve a high level of memory performance and robustness, while controlling memory consumption over time. We present experimental studies, …
Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta
Research Collection School Of Computing and Information Systems
IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes …
Eating Alone, Together: New Forms Of Commensality, Catherine Grevet, Anthony Tang, Elizabeth Mynatt
Eating Alone, Together: New Forms Of Commensality, Catherine Grevet, Anthony Tang, Elizabeth Mynatt
Research Collection School Of Computing and Information Systems
Eating with others, or commensality, is an enjoyable activity that serves many important social functions; however, many individuals eat meals alone due to life circumstances, meaning that they miss out on these social benefits. We developed and deployed a simple technology probe providing social awareness around mealtimes to explore how social systems might help alleviate the loneliness of solitary dining. Our findings suggest that these systems can convey a sense of connectedness around a meal; further, our analysis revealed three themes relevant to systems of this type: that contextually-located peripheral awareness engenders connectedness; that such tools can foster a feeling …
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is …
Credit Card Program Value Maximization With Promotion Density For Product Discounts In Shopping Malls, Rae M. Chang, Robert John Kauffman, Kwansoo Kim
Credit Card Program Value Maximization With Promotion Density For Product Discounts In Shopping Malls, Rae M. Chang, Robert John Kauffman, Kwansoo Kim
Research Collection School Of Computing and Information Systems
We model value maximization of credit card programs for shopping malls, when card customerscan obtain product discounts of different percentages in the presence of promotion density andcompetition. Our results suggest strategies for quantitatively evaluating the trade-offs in valueoutcomes when consumer sensitivity to product discounting varies.
A Feasibility Study Of Crowdsourcing And Google Street View To Determine Sidewalk Accessibility, Kotaro Hara, Victoria Le, Jon Froehlich
A Feasibility Study Of Crowdsourcing And Google Street View To Determine Sidewalk Accessibility, Kotaro Hara, Victoria Le, Jon Froehlich
Research Collection School Of Computing and Information Systems
We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work.
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Sensor Openflow: Enabling Software-Defined Wireless Sensor Networks, Tie Luo, Hwee-Pink Tan, Tony Q. S. Quek
Research Collection School Of Computing and Information Systems
While it has been a belief for over a decade that wireless sensor networks (WSN) are application-specific, we argue that it can lead to resource underutilization and counter-productivity. We also identify two other main problems with WSN: rigidity to policy changes and difficulty to manage. In this paper, we take a radical, yet backward and peer compatible, approach to tackle these problems inherent to WSN. We propose a Software-Defined WSN architecture and address key technical challenges for its core component, Sensor OpenFlow. This work represents the first effort that synergizes software-defined networking and WSN.
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos
Research Collection School Of Computing and Information Systems
Nowadays, there are many queries issued to search engines targeting at finding values from structured data (e.g., movie showtime of a specific location). In such scenarios, there is often a mismatch between the values of structured data (how content creators describe entities) and the web queries (how different users try to retrieve them). Therefore, recognizing the alternative ways people use to reference an entity, is crucial for structured web search. In this paper, we study the problem of automatic generation of entity synonyms over structured data toward closing the gap between users and structured data. We propose an offline, data-driven …
Information Retrieval Based Nearest Neighbor Classification For Fine-Grained Bug Severity Prediction, Yuan Tian, David Lo, Chengnian Sun
Information Retrieval Based Nearest Neighbor Classification For Fine-Grained Bug Severity Prediction, Yuan Tian, David Lo, Chengnian Sun
Research Collection School Of Computing and Information Systems
Bugs are prevalent in software systems. Some bugs are critical and need to be fixed right away, whereas others are minor and their fixes could be postponed until resources are available. In this work, we propose a new approach leveraging information retrieval, in particular BM25-based document similarity function, to automatically predict the severity of bug reports. Our approach automatically analyzes bug reports reported in the past along with their assigned severity labels, and recommends severity labels to newly reported bug reports. Duplicate bug reports are utilized to determine what bug report features, be it textual, ordinal, or categorical, are important. …
Predicting Common Web Application Vulnerabilities From Input Validation And Sanitization Code Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Predicting Common Web Application Vulnerabilities From Input Validation And Sanitization Code Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
Software defect prediction studies have shown that defect predictors built from static code attributes are useful and effective. On the other hand, to mitigate the threats posed by common web application vulnerabilities, many vulnerability detection approaches have been proposed. However, finding alternative solutions to address these risks remains an important research problem. As web applications generally adopt input validation and sanitization routines to prevent web security risks, in this paper, we propose a set of static code attributes that represent the characteristics of these routines for predicting the two most common web application vulnerabilities—SQL injection and cross site scripting. In …
Adaptive In-Network Processing For Bandwidth And Energy Constrained Mission-Oriented Multi-Hop Wireless Networks, Sharanya Eswaran, James Edwards, Archan Misra, Thomas La Porta
Adaptive In-Network Processing For Bandwidth And Energy Constrained Mission-Oriented Multi-Hop Wireless Networks, Sharanya Eswaran, James Edwards, Archan Misra, Thomas La Porta
Research Collection School Of Computing and Information Systems
In-network processing, involving operations such as filtering, compression and fusion, is a technique widely used in wireless sensor and ad hoc networks for reducing the communication overhead. In many tactical stream-oriented applications, especially in military scenarios, both link bandwidth and node energy are critically constrained resources. For such applications, in-network processing itself imposes non-negligible computing cost. In this work, we have developed a unified, utility-based closed-loop control framework that permits distributed convergence to both a) the optimal level of compression performed by a forwarding node on streams, and b) the best set of nodes where the operators of the stream …
No Tradeoff Between Confidentiality And Performance: An Analysis On H.264/Svc Partial Encryption, Zhuo Wei, Xuhua Ding, Robert H. Deng, Yongdong Wu
No Tradeoff Between Confidentiality And Performance: An Analysis On H.264/Svc Partial Encryption, Zhuo Wei, Xuhua Ding, Robert H. Deng, Yongdong Wu
Research Collection School Of Computing and Information Systems
Partial encryption is often used as a tradeoff between security and performance to protect scalable video data. In this paper, we argue that although partial encryption is strong enough for access control, it is not adequate for content confidentiality protection. We conduct experiments to show that partially encrypted H.264/SVC (scalable video coding) streams leak significant content information from the enhancement layers in all three scalability dimensions. Our analysis concludes that such leakage is caused by the underlying coding techniques used in H.264/SVC, and all layers should be encrypted to protect confidential video streams.
Learning Fine-Grained Structured Input For Memory Corruption Detection, Lei Zhao, Debin Gao, Lina Wang
Learning Fine-Grained Structured Input For Memory Corruption Detection, Lei Zhao, Debin Gao, Lina Wang
Research Collection School Of Computing and Information Systems
Inputs to many application and server programs contain rich and consistent structural information. The propagation of such input in program execution could serve as accurate and reliable signatures for detecting memory corruptions. In this paper, we propose a novel approach to detect memory corruptions at the binary level. The basic insight is that different parts of an input are usually processed in different ways, e.g., by different instructions. Identifying individual parts in an input and learning the pattern in which they are processed is an attractive approach to detect memory corruptions. We propose a fine-grained dynamic taint analysis system to …
Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump
Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
GP 2 is an experimental nondeterministic programming language based on graph transformation rules, allowing for visual programming and the solving of graph problems at a high-level of abstraction. In previous work we demonstrated how to verify graph programs using a Hoare-style proof calculus, but only partial correctness was considered. In this paper, we add new proof rules and termination functions, which allow for proofs to additionally guarantee that program executions always terminate (weak total correctness), or that programs always terminate and do so without failure (total correctness). We show that the new proof rules are sound with respect to the …
Verification Of Graph Programs, Christopher M. Poskitt
Verification Of Graph Programs, Christopher M. Poskitt
Research Collection School Of Computing and Information Systems
GP (for Graph Programs) is an experimental nondeterministic programming language which allows for the manipulation of graphs at a high level of abstraction. The program states of GP are directed labelled graphs. These are manipulated directly via the application of (conditional) rule schemata, which generalise double-pushout rules with expressions over labels and relabelling. In contrast with graph grammars, the application of these rule schemata is directed by a number of simple control constructs including sequential composition, conditionals, and as-long-as-possible iteration. GP shields programmers at all times from low-level implementation issues (e.g. graph representation), and with its nondeterministic semantics, allows one …
Extending A Mobile Device's Interaction Space Through Body-Centric Interaction, Xiang Chen, Nicolai Marquardt, Anthony Tang, Sebastian Boring, Saul Greenberg
Extending A Mobile Device's Interaction Space Through Body-Centric Interaction, Xiang Chen, Nicolai Marquardt, Anthony Tang, Sebastian Boring, Saul Greenberg
Research Collection School Of Computing and Information Systems
Modern mobile devices rely on the screen as a primary input modality. Yet the small screen real-estate limits interaction possibilities, motivating researchers to explore alternate input techniques. Within this arena, our goal is to develop Body-Centric Interaction with Mobile Devices: a class of input techniques that allow a person to position and orient her mobile device to navigate and manipulate digital content anchored in the space on and around the body. To achieve this goal, we explore such interaction in a bottom-up path of prototypes and implementations. From our experiences, as well as by examining related work, we discuss and …
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Nicolai Marquardt, Anthony Tang, Saul Greenberg
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Nicolai Marquardt, Anthony Tang, Saul Greenberg
Research Collection School Of Computing and Information Systems
Modern mobile devices allow a rich set of multi-finger interactions that combine modes into a single fluid act, for example, one finger for panning blending into a two-finger pinch gesture for zooming. Such gestures require the use of both hands: one holding the device while the other is interacting. While on the go, however, only one hand may be available to both hold the device and interact with it. This mostly limits interaction to a single-touch (i.e., the thumb), forcing users to switch between input modes explicitly. In this paper, we contribute the Fat Thumb interaction technique, which uses the …
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Anthony Tang, Anthony Tang, Saul Greenberg
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Anthony Tang, Anthony Tang, Saul Greenberg
Research Collection School Of Computing and Information Systems
Modern mobile devices allow a rich set of multi-finger interactions that combine modes into a single fluid act. Such gestures may require the use of both hands: one holding the device while the other is interacting. While on the go, however, only one hand may be available to both hold the device and interact with it. In this demo, we present the Fat Thumb interaction technique, which uses the thumb's contact size as a form of simulated pressure. We present how this can be used, for example, to integrate panning and zooming into a single interaction. Contact size determines the …