Computer Sciences Commons^™

Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Susnagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological- inspired dual memory model for agents, consisting of an episodic memory that records the agent's experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not …

Fast Semantic Diffusion For Large-Scale Context-Based Image And Video Annotation, Yu-Gang Jiang, Qi Dai, Jun Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Exploring context information for visual recognition has recently received significant research attention. This paper proposes a novel and highly efficient approach, which is named semantic diffusion, to utilize semantic context for large-scale image and video annotation. Starting from the initial annotation of a large number of semantic concepts (categories), obtained by either machine learning or manual tagging, the proposed approach refines the results using a graph diffusion technique, which recovers the consistency and smoothness of the annotations over a semantic graph. Different from the existing graph-based learning methods that model relations among data samples, the semantic graph captures context by …

Sammple: Detecting Semantic Indoor Activities In Practical Settings Using Locomotive Signatures, Zhixian Yan, Dipanjan Chakraborty, Archan Misra, Hoyoung Jeung, Karl Aberer

Research Collection School Of Computing and Information Systems

We analyze the ability of mobile phone-generated accelerometer data to detect high-level (i.e., at the semantic level) indoor lifestyle activities, such as cooking at home and working at the workplace, in practical settings. We design a 2-T ier activity extraction framework (called SAMMPLE) for our purpose. Using this, we evaluate discriminatory power of activity structures along the dimension of statistical features and after a transformation to a sequence of individual locomotive micro-activities (e.g. sitting or standing). Our findings from 152 days of real-life behavioral traces reveal that locomotive signatures achieve an average accuracy of 77.14%, an improvement of 16.37% over …

Are Faults Localizable?, Lucia Lucia, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many fault localization techniques have been proposed to facilitate debugging activities. Most of them attempt to pinpoint the location of faults (i.e., localize faults) based on a set of failing and correct executions and expect debuggers to investigate a certain number of located program elements to find faults. These techniques thus assume that faults are localizable, i.e., only one or a few lines of code that are close to one another are responsible for each fault. However, in reality, are faults localizable? In this work, we investigate hundreds of real faults in several software systems, and find that many faults …

Vertical Differentiation And A Comparison Of Online Advertising Models, Mei Lin, Xuqing Ke, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

Designing business models that take into consideration the role of advertising support is critical to the success of online services. In this paper, we address the challenges of these business model strategies and compare different ad revenue models. We use game theory to model vertical differentiation in both monopoly and duopoly settings, in which online service providers may offer an ad-free service, an ad-supported service, or a combination of these services. Offering both ad-free and ad-supported services is the optimal strategy for a monopolist because ad revenues compensate for the cannibalistic effect of vertical differentiation. In a duopoly equilibrium, exactly …

Complexity Of The Soundness Problem Of Bounded Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Classical workflow nets (WF-nets) are an important class of Petri nets that are widely used to model and analyze workflow systems. Soundness is a crucial property that guarantees these systems are deadlock-free and bounded. Aalst et al. proved that the soundness problem is decidable, and proposed (but not proved) that the soundness problem is EXPSPACE-hard. In this paper, we show that the satisfiability problem of Boolean expression is polynomial time reducible to the liveness problem of bounded WF-nets, and soundness and liveness are equivalent for bounded WF-nets. As a result, the soundness problem of bounded WF-nets is co-NP-hard.Workflow nets with …

Ifalcon: A Neural Architecture For Hierarchical Planning, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Hierarchical planning is an approach of planning by composing and executing hierarchically arranged predefined plans on the fly to solve some problems. This approach commonly relies on a domain expert providing all semantic and structural knowledge. One challenge is how the system deals with incomplete ill-defined knowledge while the solution can be achieved on the fly. Most symbolic-based hierarchical planners have been devised to allow the knowledge to be described expressively. However, in some cases, it is still difficult to produce the appropriate knowledge due to the complexity of the problem domain especially if the missing knowledge must be acquired …

A Self-Organizing Multi-Memory System For Autonomous Agents, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Yuan-Sin Tan

Research Collection School Of Computing and Information Systems

This paper presents a self-organizing approach to the learning of procedural and declarative knowledge in parallel using independent but interconnected memory models. The proposed system, employing fusion Adaptive Resonance Theory (fusion ART) network as a building block, consists of a declarative memory module, that learns both episodic traces and semantic knowledge in real time, as well as a procedural memory module that learns reactive responses to its environment through reinforcement learning. More importantly, the proposed multi-memory system demonstrates how the various memory modules transfer knowledge and cooperate with each other for a higher overall performance. We present experimental studies, wherein …

Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria

Research Collection School Of Computing and Information Systems

Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive balanced news information is important. We propose a model that maps the news media sources along a dimensional dichotomous political spectrum using the co-subscriptions relationships inferred by Twitter links. By analyzing 7 million follow links, we show that the political dichotomy naturally arises on Twitter when we only consider direct media subscription. Furthermore, we demonstrate a real-time Twitter-based application …

Mining Quantified Temporal Rules: Formalism, Algorithms, And Evaluation, David Lo, Ganesan Ramalingam, Venkatesh Prasad Ranganath, Kapil Vaswani

Research Collection School Of Computing and Information Systems

Libraries usually impose constraints on how clients should use them. Often these constraints are not well-documented. In this paper, we address the problem of recovering such constraints automatically, a problem referred to as specification mining. Given some client programs that use a given library, we identify constraints on the library usage that are (almost) satisfied by the given set of clients.The class of rules we target for mining combines simple binary temporal operators with state predicates (composed of equality constraints) and quantification. This is a simple yet expressive subclass of temporal properties (LTL formulae) that allows us to capture many …

Mobicon: Mobile Context Monitoring Platform: Incorporating Context-Awareness To Smartphone-Centric Personal Sensor Networks, Youngki Lee, Younghyun Ju, Chuihong Min, Jihun Yu, Junehwa Song

Research Collection School Of Computing and Information Systems

In this demonstration, we will show MobiCon, a context monitoring platform; it runs over smartphones and sensor OSs, and facilitates development and deployment of everyday context-aware applications. For many years, lots of research efforts have been made in building low-cost, yet effective sensor networks for various application domains such as structural health monitoring of bridges, disaster recovery, automated ventilation of buildings. Integration of sensors into smartphones and the advent of wearable devices open a new opportunity for mobile applications to leverage in-situ user contexts such as his/her location, activity, social relationship, health status. In recent studies of mobile and pervasive …

Stochastic Dominance In Stochastic Dcops For Risk-Sensitive Applications, Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are well-suited for modeling multi-agent coordination problems where the primary interactions are between local subsets of agents. However, one limitation of DCOPs is the assumption that the constraint rewards are without uncertainty. Researchers have thus extended DCOPs to Stochastic DCOPs (SDCOPs), where rewards are sampled from known probability distribution reward functions, and introduced algorithms to find solutions with the largest expected reward. Unfortunately, such a solution might be very risky, that is, very likely to result in a poor reward. Thus, in this paper, we make three contributions: (1) we propose a stricter objective for …

Distributed Incomplete Pattern Matching Via A Novelweighted Bloom Filter, Siyuan Liu, Lei Kang, Lei Chen, Lionel Ni

Research Collection School Of Computing and Information Systems

In this paper, we first propose a very interesting and practical problem, pattern matching in a distributed mobile environment. Pattern matching is a well-known problem and extensive research has been conducted for performing effective and efficient search. However, previous proposed approaches assume that data are centrally stored, which is not the case in a mobile environment (e.g., mobile phone networks), where one person’s pattern could be separately stored in a number of different stations, and such a local pattern is incomplete compared with the global pattern. A simple solution to pattern matching over a mobile environment is to collect all …

When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong

Research Collection School Of Computing and Information Systems

Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According …

Self-Organizing Neural Networks For Learning Air Combat Maneuvers, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper reports on an agent-oriented approach for the modeling of adaptive doctrine-equipped computer generated force (CGF) using a commercial-grade simulation platform known as CAE STRIVECGF. A self- organizing neural network is used for the adaptive CGF to learn and generalize knowledge in an online manner during the simulation. The challenge of defining the state space and action space and the lack of domain knowledge to initialize the adaptive CGF are addressed using the doctrine used to drive the non-adaptive CGF. The doctrine contains a set of specialized knowledge for conducting 1-v-1 dogfights. The hierarchical structure and symbol representation of …

Semi-Supervised Hierarchical Clustering For Personalized Web Image Organization, Lei Meng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Existing efforts on web image organization usually transform the task into surrounding text clustering. However, Current text clustering algorithms do not address the problem of insufficient statistical information for image representation and noisy tags which greatly decreases the clustering performance while increases the computational cost. In this paper, we propose a two-step semi-supervised hierarchical clustering algorithm, Personalized Hierarchical Theme-based Clustering (PHTC), for web image organization. In the first step, the Probabilistic Fusion ART (PF-ART) is proposed for grouping semantically similar images and simultaneously learning the probabilistic distribution of tag occurrence for mining the key tags/topics of clusters. In this way, …

A Novel Unbalanced Tree Structure For Low-Cost Authentication Of Streaming Content On Mobile And Sensor Devices, Thivya Kandappu, Vijay Sivaraman, Roksana Boreli

Research Collection School Of Computing and Information Systems

We consider stored content being streamed to a resource-poor device (such as a sensor node or a mobile phone), and address the issue of authenticating such content in realtime at the receiver. Per-packet digital signatures incur high computational cost, while per-block signatures impose high delays. A Merkle hash tree combines the benefits of the two by having a single signature per-block (at the root of the tree), while allowing immediate per-packet verification by following a hash-path logarithmic in the number of packets. In this paper we explore how the structure of the Merkle tree can be adapted to improve playback …

Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac Sreenan, Chun Tung Chou, Archan Misra, Sanjay Jha

Research Collection School Of Computing and Information Systems

This paper studies video multicasting in large scale areas using wireless mesh networks. The focus is on the use of Internet access gateways that allow a choice of alternative routes to avoid potentially lengthy and low capacity multi-hop wireless paths. A set of heuristic-based algorithms are described that together aim to maximize network capacity: the two-tier integrated architecture algorithm, the weighted gateway uploading algorithm, the link controlled routing tree algorithm, and the dynamic group management algorithm. These algorithms use different approaches to arrange nodes involved in video multicasting into a clustered and two-tier integrated architecture in which network protocols can …

Comon: Cooperative Ambience Monitoring Platform With Continuity And Benefit Awareness, Youngki Lee, Younghyun Ju, Chulhong Min, Seungwoo Kang, Inseok Hwang, Junehwa Song

Research Collection School Of Computing and Information Systems

Mobile applications that sense continuously, such as location monitoring, are emerging. Despite their usefulness, their adoption in real-world deployment situations has been extremely slow. Many smartphone users are turned away by the drastic battery drain caused by continuous sensing and processing. Also, the extractable contexts from the phone are quite limited due to its position and sensing modalities. In this paper, we propose CoMon, a novel cooperative ambience monitoring platform, which newly addresses the energy problem through opportunistic cooperation among nearby mobile users. To maximize the benefit of cooperation, we develop two key techniques, (1) continuity-aware cooperator detection and (2) …

Delayed Observation Planning In Partially Observable Domains, Pradeep Reddy Varakantham, Janusz Marecki

Research Collection School Of Computing and Information Systems

Traditional models for planning under uncertainty such as Markov Decision Processes (MDPs) or Partially Observable MDPs (POMDPs) assume that the observations about the results of agent actions are instantly available to the agent. In so doing, they are no longer applicable to domains where observations are received with delays caused by temporary unavailability of information (e.g. delayed response of the market to a new product). To that end, we make the following key contributions towards solving Delayed observation POMDPs (D-POMDPs): (i) We first provide an parameterized approximate algorithm for solving D-POMDPs efficiently, with desired accuracy; and (ii) We then propose …

Adaptive Data Acquisition Strategies For Energy-Efficient, Smartphone-Based, Continuous Processing Of Sensor Streams, Lipyeow Lim, Archan Misra, Tianli Mo

Research Collection School Of Computing and Information Systems

There is a growing interest in applications that utilize continuous sensing of individual activity or context, via sensors embedded or associated with personal mobile devices (e.g., smartphones). Reducing the energy overheads of sensor data acquisition and processing is essential to ensure the successful continuous operation of such applications, especially on battery-limited mobile devices. To achieve this goal, this paper presents a framework, called ACQUA, for ‘acquisition-cost’ aware continuous query processing. ACQUA replaces the current paradigm, where the data is typically streamed (pushed) from the sensors to the one or more smartphones, with a pull-based asynchronous model, where a smartphone retrieves …

Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo

Research Collection School Of Computing and Information Systems

In the evolution of an operating system there is a continuing tension between the need to develop and test new features, and the need to provide a stable and secure execution environment to users. A compromise, adopted by the developers of the Linux kernel, is to release new versions, including bug fixes and new features, frequently, while maintaining some older “longterm” versions. This strategy raises the problem of how to identify bug fixing patches that are submitted to the current version but should be applied to the longterm versions as well. The current approach is to rely on the individual …

Active Refinement Of Clone Anomaly Reports, Lucia, David Lo, Lingxiao Jiang, Aditya Budi

Research Collection School Of Computing and Information Systems

Software clones have been widely studied in the recent literature and shown useful for finding bugs because inconsistent changes among clones in a clone group may indicate potential bugs. However, many inconsistent clone groups are not real bugs (true positives). The excessive number of false positives could easily impede broad adoption of clone-based bug detection approaches. In this work, we aim to improve the usability of clone-based bug detection tools by increasing the rate of true positives found when a developer analyzes anomaly reports. Our idea is to control the number of anomaly reports a user can see at a …

Modeling Diffusion In Social Networks Using Network Properties, Duc Minh Luu, Ee Peng Lim, Tuan Anh Hoang, Chong Tat Freddy Chua

Research Collection School Of Computing and Information Systems

"Diffusion of items occurs in social networks due to spreading of items through word of mouth and exogenous factors. These items may be news, products, videos, advertisements or contagious viruses. When a user purchases or consumes one of such items, we say that she adopts the item and she becomes an item adopter. Previous research has studied diffusion process at both the macro and micro levels. The former models the number of item adopters in the diffusion process while the latter determines which individuals adopt item. Both macro and micro level models have their merits and limitations. In this paper, …

Dash: A Novel Search Engine For Database-Generated Dynamic Web Pages, Ken C. K. Lee, Kanchan Bankar, Baihua Zheng, Chi-Yin Chow, Honggang Wang

Research Collection School Of Computing and Information Systems

Database-generated dynamic web pages (db-pages, in short), whose contents are created on the fly by web applications and databases, are now prominent in the web. However, many of them cannot be searched by existing search engines. Accordingly, we develop a novel search engine named Dash, which stands for Db-pAge SearcH, to support db-page search. Dash determines db-pages possibly generated by a target web application and its database through exploring the application code and the related database content and supports keyword search on those db-pages. In this paper, we present its system design and focus on the efficiency issue.

To minimize …

Trurepec: A Trust-Behavior-Based Reputation And Recommender System For Mobile Applications, Zheng Yan, Peng Zhang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Mobile applications are software packages that can be installed and executed in a mobile device. Which mobile application is trustworthy for a user to purchase, download, install, execute or recommend becomes a crucial issue that impacts its final success. This paper proposes TruBeRepec, a trust-behavior-based reputation and recommender system for mobile applications. We explore a model of trust behavior for mobile applications based on the result of a large-scale user survey. We further develop a number of algorithms that are used to evaluate individual user’s trust in a mobile application through trust behavior observation, generate the application’s reputation by aggregating …

A New Framework For Privacy Of Rfid Path Authentication, Shaoying Cai, Robert H. Deng, Yingjiu Li, Yunlei Zhao

Research Collection School Of Computing and Information Systems

RFID-based path authentication enables supply chain managers to verify the exact path that a tag has taken. In this paper, we introduce a new oracle Move that models a tag's movement along a designed or an arbitrary path in a supply chain. With this oracle, we refine the existing security and privacy notions for RFID-based path authentication. In addition, we propose a new privacy notion, called path privacy, for RFID-based path authentication. Our privacy notion captures the privacy of both tag identity and path information in a single game. Compared to existing two-game based privacy notions, it is more rigorous, …

Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong

Research Collection School Of Computing and Information Systems

Cyber security is increasingly important for defending computer systems from loss of privacy or unauthorised use. One important aspect is threat analysis - how does an attacker infiltrate a system and what do they want once they are inside. This paper considers the problem of Active Malware Analysis, where we learn about the human or software intruder by actively interacting with it with the goal of learning about its behaviours and intentions, whilst at the same time that intruder may be trying to avoid detection or showing those behaviours and intentions. This game-theoretic active learning is then used to obtain …

Energy-Efficient Continuous Activity Recognition On Mobile Phones: An Activity-Adaptive Approach, Zhixian Yan, Vigneshwaran Subbaraju, Dipanjan Chakraborty, Archan Misra, Karl Aberer

Research Collection School Of Computing and Information Systems

Power consumption on mobile phones is a painful obstacle towards adoption of continuous sensing driven applications, e.g., continuously inferring individual’s locomotive activities (such as ‘sit’, ‘stand’ or ‘walk’) using the embedded accelerometer sensor. To reduce the energy overhead of such continuous activity sensing, we first investigate how the choice of accelerometer sampling frequency & classification features affects, separately for each activity, the “energy overhead” vs. “classification accuracy” tradeoff. We find that such tradeoff is activity specific. Based on this finding, we introduce an activity-sensitive strategy (dubbed “A3R” – Adaptive Accelerometer-based Activity Recognition) for continuous activity recognition, where the choice of …

What Does Software Engineering Community Microblog About?, Yuan Tian, Palakorn Achananuparp, Ibrahim Nelman Lubis, David Lo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging is a new trend to communicate and to disseminate information. One microblog post could potentially reach millions of users. Millions of microblogs are generated on a daily basis on popular sites such as Twitter. The popularity of microblogging among programmers, software engineers, and software users has also led to their use of microblogs to communicate software engineering issues apart from using emails and other traditional communication channels.Understanding how millions of users use microblogs in software engineering related activities would shed light on ways we could leverage the fast evolving microblogging content to aid software development efforts. In this work, …