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Articles 6751 - 6780 of 7453
Full-Text Articles in Physical Sciences and Mathematics
On In-Network Synopsis Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang
On In-Network Synopsis Join Processing For Sensor Networks, Hai Yu, Ee Peng Lim, Jun Zhang
Research Collection School Of Computing and Information Systems
The emergence of sensor networks enables applications that deploy sensors to collaboratively monitor environment and process data collected. In some scenarios, we are interested in using join queries to correlate data stored in different regions of a sensor network, where the data volume is large, making it prohibitive to transmit all data to a central server for joining. In this paper, we present an in-network synopsis join strategy for evaluating join queries in sensor networks with communication efficiency. In this strategy, we prune data that do not contribute to the join results in the early stage of the join processing, …
Osprey: A Practical Type System For Validating Dimensional Unit Correctness Of C Programs, Lingxiao Jiang, Zhendong Su
Osprey: A Practical Type System For Validating Dimensional Unit Correctness Of C Programs, Lingxiao Jiang, Zhendong Su
Research Collection School Of Computing and Information Systems
Misuse of measurement units is a common source of errors in scientific applications, but standard type systems do not prevent such errors. Dimensional analysis in physics can be used to manually detect such errors in physical equations. It is, however, not feasible to perform such manual analysis for programs computing physical equations because of code complexity. In this paper, we present a type system to automatically detect potential errors involving measurement units. It is constraint-based: we model units as types and flow of units as constraints. However, standard type checking algorithms are not powerful enough to handle units because of …
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Profile Likelihood Estimation Of Partially Linear Panel Data Models With Fixed Effects, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We consider consistent estimation of partially linear panel data models with fixed effects. We propose profile-likelihood-based estimators for both the parametric and nonparametric components in the models and establish convergence rates and asymptotic normality for both estimators.
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Winning Back The Cup For Distributed Pomdps: Planning Over Continuous Belief Spaces, Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo
Research Collection School Of Computing and Information Systems
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms have been proposed to obtain locally or globally optimal policies. Unfortunately, most of these algorithms have either been explicitly designed or experimentally evaluated assuming knowledge of a starting belief point, an assumption that often does not hold in complex, uncertain domains. Instead, in such domains, it is important for agents to explicitly plan over continuous belief spaces. This paper provides a novel algorithm to explicitly compute finite horizon policies over continuous belief spaces, without restricting the space of …
Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Discovering Causal Dependencies In Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Mobile context-aware recommender systems face unique challenges in acquiring context. Resource limitations make minimizing context acquisition a practical need, while the uncertainty inherent to the mobile environment makes missing context values a major concern. This paper introduces a scalable mechanism based on Bayesian network learning in a tiered context model to overcome both of these challenges. Extensive experiments on a restaurant recommender system showed that our mechanism can accurately discover causal dependencies among context, thereby enabling the effective identification of the minimal set of important context for a specific user and task, as well as providing highly accurate recommendations even …
Time-Dependent Semantic Similarity Measure Of Queries Using Historical Click-Through Data, Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma
Time-Dependent Semantic Similarity Measure Of Queries Using Historical Click-Through Data, Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma
Research Collection School Of Computing and Information Systems
It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of click-through data logged by Web search engines, which record the interactions between users and the search engines. Most existing approaches employ the click-through data for similarity measure of queries with little consideration of the temporal factor, while the click-through data is often dynamic and contains rich temporal information. In this paper we present a new framework of time-dependent query semantic similarity model on exploiting the temporal characteristics of historical click-through data. The intuition is that more accurate semantic similarity values between …
Efficient Querying And Resource Management Using Distributed Presence Information In Converged Networks, Dipanjan Chakraborty, Koustuv Dasgupta, Archan Misra
Efficient Querying And Resource Management Using Distributed Presence Information In Converged Networks, Dipanjan Chakraborty, Koustuv Dasgupta, Archan Misra
Research Collection School Of Computing and Information Systems
Next-generation converged networks shall deliver many innovative services over the standardized SIPbased IMS signaling infrastructure. Several such services exploit the joint presence information of a consumer, i.e. SIP entity requesting a service, and a vendor, i.e. SIP resource providing a service. Presence information is a collection of contextual attributes (e.g. location, availability, reputation), some of which change dynamically. Moreover, this collective presence information is distributed across multiple presence servers. While performing query matching based on joint presence information, a server usually routes each query to a locally available resource. However, skews in the spatio-temporal distribution of queries and resources may …
Mining Rdf Metadata For Generalized Association Rules: Knowledge Discovery In The Semantic Web Era, Tao Jiang, Ah-Hwee Tan
Mining Rdf Metadata For Generalized Association Rules: Knowledge Discovery In The Semantic Web Era, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of emphgeneralization closure for systematic over-generalization reduction.
Large-Scale Text Categorization By Batch Mode Active Learning, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Large-Scale Text Categorization By Batch Mode Active Learning, Steven C. H. Hoi, Rong Jin, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the human efforts in labeling text documents for building reliable classification models. In the past, there have been many studies on applying active learning methods to automatic text categorization, which try to select the most informative documents for labeling manually. Most of these studies focused on selecting a single unlabeled document in each iteration. As a result, the text categorization model has to be retrained after each labeled document is solicited. In this paper, we present …
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Gestalt-Based Feature Similarity Measure In Trademark Database, Hui Jiang, Chong-Wah Ngo, Hung-Khoon Tan
Research Collection School Of Computing and Information Systems
Motivated by the studies in Gestalt principle, this paper describes a novel approach on the adaptive selection of visual features for trademark retrieval. We consider five kinds of visual saliencies: symmetry, continuity, proximity, parallelism and closure property. The first saliency is based on Zernike moments, while the others are modeled by geometric elements extracted illusively as a whole from a trademark. Given a query trademark, we adaptively determine the features appropriate for retrieval by investigating its visual saliencies. We show that in most cases, either geometric or symmetric features can give us good enough accuracy. To measure the similarity of …
Anonymous Signature Schemes, Guomin Yang, Duncan S. Wong, Xiaotie Deng, Huaxiong Wang
Anonymous Signature Schemes, Guomin Yang, Duncan S. Wong, Xiaotie Deng, Huaxiong Wang
Research Collection School Of Computing and Information Systems
Digital signature is one of the most important primitives in public key cryptography. It provides authenticity, integrity and non-repudiation to many kinds of applications. On signer privacy however, it is generally unclear or suspicious of whether a signature scheme itself can guarantee the anonymity of the signer. In this paper, we give some affirmative answers to it. We formally define the signer anonymity for digital signature and propose some schemes of this type. We show that a signer anonymous signature scheme can be very useful by proposing a new anonymous key exchange protocol which allows a client Alice to establish …
Efficient Client-To-Server Assignments For Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Efficient Client-To-Server Assignments For Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Research Collection School Of Computing and Information Systems
Distributed Virtual Environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently assign …
A Unified Log-Based Relevance Feedback Scheme For Image Retrieval, Steven Hoi, Michael R. Lyu, Rong Jin
A Unified Log-Based Relevance Feedback Scheme For Image Retrieval, Steven Hoi, Michael R. Lyu, Rong Jin
Research Collection School Of Computing and Information Systems
Relevance feedback has emerged as a powerful tool to boost the retrieval performance in content-based image retrieval (CBIR). In the past, most research efforts in this field have focused on designing effective algorithms for traditional relevance feedback. Given that a CBIR system can collect and store users' relevance feedback information in a history log, an image retrieval system should be able to take advantage of the log data of users' feedback to enhance its retrieval performance. In this paper, we propose a unified framework for log-based relevance feedback that integrates the log of feedback data into the traditional relevance feedback …
Fisa: Feature-Based Instance Selection For Imbalanced Text Classification, Aixin Sun, Ee Peng Lim, Boualem Benatallah, Mahbub Hassan
Fisa: Feature-Based Instance Selection For Imbalanced Text Classification, Aixin Sun, Ee Peng Lim, Boualem Benatallah, Mahbub Hassan
Research Collection School Of Computing and Information Systems
Support Vector Machines (SVM) classifiers are widely used in text classification tasks and these tasks often involve imbalanced training. In this paper, we specifically address the cases where negative training documents significantly outnumber the positive ones. A generic algorithm known as FISA (Feature-based Instance Selection Algorithm), is proposed to select only a subset of negative training documents for training a SVM classifier. With a smaller carefully selected training set, a SVM classifier can be more efficiently trained while delivering comparable or better classification accuracy. In our experiments on the 20-Newsgroups dataset, using only 35% negative training examples and 60% learning …
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Evaluation Of Time-Varying Availability In Multi-Echelon Spare Parts Systems With Passivation, Hoong Chuin Lau, Huawei Song, Chuen Teck See, Siew Yen Cheng
Research Collection School Of Computing and Information Systems
The popular models for repairable item inventory, both in the literature as well as practical applications, assume that the demands for items are independent of the number of working systems. However this assumption can introduce a serious underestimation of availability when the number of working systems is small, the failure rate is high or the repair time is long. In this paper, we study a multi-echelon repairable item inventory system under the phenomenon of passivation, i.e. serviceable items are passivated (“switched off”) upon system failure. This work is motivated by corrective maintenance of high-cost technical equipment in the miltary. We …
A Practical Password-Based Two-Server Authentication And Key Exchange System, Yanjiang Yang, Robert H. Deng, Feng Bao
A Practical Password-Based Two-Server Authentication And Key Exchange System, Yanjiang Yang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Most password-based user authentication systems place total trust on the authentication server where cleartext passwords or easily derived password verification data are stored in a central database. Such systems are, thus, by no means resilient against offline dictionary attacks initiated at the server side. Compromise of the authentication server by either outsiders or insiders subjects all user passwords to exposure and may have serious legal and financial repercussions to an organization. Recently, several multiserver password systems were proposed to circumvent the single point of vulnerability inherent in the single-server architecture. However, these multiserver systems are difficult to deploy and operate …
Enterprise Agility And The Enabling Role Of Information Technology, Eric Overby, Anandhi S. Bharadwaj, V. Sambamurthy
Enterprise Agility And The Enabling Role Of Information Technology, Eric Overby, Anandhi S. Bharadwaj, V. Sambamurthy
Research Collection School Of Computing and Information Systems
In turbulent environments, enterprise agility, that is, the ability of firms to sense environmental change and respond readily, is an important determinant of firm success. We define and deconstruct enterprise agility, delineate enterprise agility from similar concepts in the business research literature, explore the underlying capabilities that support enterprise agility, explicate the enabling role of information technology (IT) and digital options, and propose a method for measuring enterprise agility. The concepts in this paper are offered as foundational building blocks for the overall research program on enterprise agility and the enabling role of IT.
Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu
Searching Substructures With Superimposed Distance, Xifeng Yan, Feida Zhu, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a …
In-Network Processing Of Nearest Neigbor Queries For Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
In-Network Processing Of Nearest Neigbor Queries For Wireless Sensor Networks, Yuxia Yao, Xueyan Tang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Wireless sensor networks have been widely used for civilian and military applications, such as environmental monitoring and vehicle tracking. The sensor nodes in the network have the abilities to sense, store, compute and communicate. To enable object tracking applications, spatial queries such as nearest neighbor queries are to be supported in these networks. The queries can be injected by the user at any sensor node. Due to the limited power supply for sensor nodes, energy efficiency is the major concern in query processing. Centralized data storage and query processing schemes do not favor energy efficiency. In this paper, we propose …
Experimental And Empirical Perspectives On Grid Resource Allocation For The Singapore Market, Danny Oh, Steven Miller, Nan Hu
Experimental And Empirical Perspectives On Grid Resource Allocation For The Singapore Market, Danny Oh, Steven Miller, Nan Hu
Research Collection School Of Computing and Information Systems
In this paper, we describe our work on using the Tycoon system developed by HP Labs to provide a market-based resource allocation and bidding framework for a grid. We discuss how we intend to evaluate the feasibility of the Tycoon system by measuring its economic performance using agent-based simulation experiments for a particular type of grid usage scenario, namely, the digital media market scenario. We will also discuss a related effort in collecting and using real grid data from the National Grid Pilot Platform in Singapore and how we will be using real data collected to derive actual usage patterns …
Sgpm: Static Group Pattern Mining Using Apriori-Like Sliding Window, John Goh, David Taniar, Ee Peng Lim
Sgpm: Static Group Pattern Mining Using Apriori-Like Sliding Window, John Goh, David Taniar, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Mobile user data mining is a field that focuses on extracting interesting pattern and knowledge out from data generated by mobile users. Group pattern is a type of mobile user data mining method. In group pattern mining, group patterns from a given user movement database is found based on spatio-temporal distances. In this paper, we propose an improvement of efficiency using area method for locating mobile users and using sliding window for static group pattern mining. This reduces the complexity of valid group pattern mining problem. We support the use of static method, which uses areas and sliding windows instead …
Effect Of Changing Requirements: A Tracking Mechanism For The Analysis Workflow, Subhajit Datta, Robert Van Engelen
Effect Of Changing Requirements: A Tracking Mechanism For The Analysis Workflow, Subhajit Datta, Robert Van Engelen
Research Collection School Of Computing and Information Systems
Managing the effects of changing requirements remains one of the greatest challenges of enterprise software development. The iterative and incremental model provides an expedient framework for addressing such concerns. This paper presents a set of metrics - Mutation Index, Component Set, Dependency Index - and a methodology to measure the effects of requirement changes in the analysis workflow from one iteration to another. Results from a sample case study are included to highlight a usage scenario. Future directions of our work based on this mechanism are also discussed.
Fortifying Password Authentication In Integrated Healthcare Delivery Systems, Yanjiang Yang, Robert H. Deng, Feng Bao
Fortifying Password Authentication In Integrated Healthcare Delivery Systems, Yanjiang Yang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Integrated Delivery Systems (IDSs) now become a primary means of care provision in healthcare domain. However, existing password systems (under either the single-server model or the multi-server model) do not provide adequate security when applied to IDSs. We are thus motivated to present a practical password authentication system built upon a novel two-server model. We generalize the two-server model to an architecture of a single control server supporting multiple service servers, tailored to the organizational structure of IDSs. The underlying user authentication and key exchange protocols we propose are password-only, neat, efficient, and robust against off-line dictionary attacks mounted by …
Robust Classification Of Eeg Signal For Brain-Computer Interface, Manoj Thulasidas, Cuntai Guan, Jiankang Wu
Robust Classification Of Eeg Signal For Brain-Computer Interface, Manoj Thulasidas, Cuntai Guan, Jiankang Wu
Research Collection School Of Computing and Information Systems
We report the implementation of a text input application (speller) based on the P300 event related potential. We obtain high accuracies by using an SVM classifier and a novel feature. These techniques enable us to maintain fast performance without sacrificing the accuracy, thus making the speller usable in an online mode. In order to further improve the usability, we perform various studies on the data with a view to minimizing the training time required. We present data collected from nine healthy subjects, along with the high accuracies (of the order of 95% or more) measured online. We show that the …
Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta
Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta
Research Collection School Of Computing and Information Systems
Aspect Oriented Programming (AOP) provides powerful techniques for modeling and implementing enterprise software systems. To leverage its full potential, AOP needs to be perceived in the context of existing methodologies such as Object Oriented Programming (OOP). This paper addresses an important question for AOP practitioners - how to decide whether a component is best modeled as a class or an aspect? Towards that end, we present an indicator metric, the Crosscutting Score and a method for its calculation and interpretation. We will illustrate our approach through a sample calculation.
Tacit Knowledge, Nonaka And Takeuchi Seci Model And Informal Knowledge Processes, Siu Loon Hoe
Tacit Knowledge, Nonaka And Takeuchi Seci Model And Informal Knowledge Processes, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
The organizational behavior and knowledge management literature has devoted a lot attention on how structural knowledge processes enhance learning. There has been little emphasis on the informal knowledge processes and the construct remains undefined. The purpose of this paper is to highlight the importance of informal knowledge processes, propose a definition for these processes and link them to the socialization and internalization processes suggested by Nonaka and Takeuchi in the SECI model. The paper offers a fresh perspective on how informal knowledge processes in organizations help to enhance the organization’s learning capability. It will enable scholars and managers to have …
Publicly Verifiable Ownership Protection For Relational Databases, Yingjiu Li, Robert H. Deng
Publicly Verifiable Ownership Protection For Relational Databases, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Today, watermarking techniques have been extended from the multimedia context to relational databases so as to protect the ownership of data even after the data are published or distributed. However, all existing watermarking schemes for relational databases are secret key based, thus require a secret key to be presented in proof of ownership. This means that the ownership can only be proven once to the public (e.g., to the court). After that, the secret key is known to the public and the embedded watermark can be easily destroyed by malicious users. Moreover, most of the existing techniques introduce distortions to …
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li
Research Collection School Of Computing and Information Systems
This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary
A Hybrid Scatter Search/Electromagnetism Meta-Heuristic For Project Scheduling, Dieter Debels, Bert De Reyck, Roel Leus, Mario Vanhoucke
A Hybrid Scatter Search/Electromagnetism Meta-Heuristic For Project Scheduling, Dieter Debels, Bert De Reyck, Roel Leus, Mario Vanhoucke
Research Collection Lee Kong Chian School Of Business
In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions for relatively large instances. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and from a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory. We present computational …
Caps: Energy-Efficient Processing Of Continuous Aggregate Queries In Sensor Networks, Wen Hu, Archan Misra, Rajiv Shorey
Caps: Energy-Efficient Processing Of Continuous Aggregate Queries In Sensor Networks, Wen Hu, Archan Misra, Rajiv Shorey
Research Collection School Of Computing and Information Systems
In this paper, we design and evaluate an energy efficient data retrieval architecture for continuous aggregate queries in wireless sensor networks. We show how the modification of precision in one sensor affects the sample-reporting frequency of other sensors, and how the precisions of a group of sensors may be collectively modified to achieve the target quality of information (QoI) with higher energy-efficiency. The proposed collective adaptive precision setting (CAPS) architecture is then extended to exploit the observed temporal correlation among successive sensor samples for even greater energy efficiency. Detailed simulations with synthetic and real data traces demonstrate how the combination …