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Research Collection School Of Computing and Information Systems

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Articles 5971 - 6000 of 6891

Full-Text Articles in Physical Sciences and Mathematics

A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun Apr 2008

A Formal Model Of Semantic Web Service Ontology (Wsmo) Execution, Hai H. Wang, Nick Gibbins, Terry R. Payne, Ahmed Saleh, Jun Sun

Research Collection School Of Computing and Information Systems

Semantic Web services have been one of the most significant research areas within the semantic Web vision, and have been recognized as a promising technology that exhibits huge commercial potential. Current semantic Web service research focuses on defining models and languages for the semantic markup of all relevant aspects of services, which are accessible through a Web service interface. The Web service modelling ontology (WSMO) is one of the most significant semantic Web service framework proposed to date. To support the standardization and tool support of WSMO, a formal semantics of the language is highly desirable. As there are a …

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Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava Apr 2008

Building A Web Of Trust Without Explicit Trust Ratings, Young Ae Kim, Minh-Tam Le, Hady W. Lauw, Ee Peng Lim, Haifeng Liu, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

A satisfactory and robust trust model is gaining importance in addressing information overload, and helping users collect reliable information in online communities. Current research on trust prediction strongly relies on a web of trust, which is directly collected from users based on previous experience. However, the web of trust is not always available in online communities and even though it is available, it is often too sparse to predict the trust value between two unacquainted people with high accuracy. In this paper, we propose a framework to derive degree of trust based on users' expertise and users' affinity for certain …

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Validating Multi-Column Schema Matchings By Type, Bing Tian Dai, Nick Koudas, Divesh Srivastava, Anthony K.H. Tung, Suresh Venkatasubramanian Apr 2008

Validating Multi-Column Schema Matchings By Type, Bing Tian Dai, Nick Koudas, Divesh Srivastava, Anthony K.H. Tung, Suresh Venkatasubramanian

Research Collection School Of Computing and Information Systems

Validation of multi-column schema matchings is essential for successful database integration. This task is especially difficult when the databases to be integrated contain little overlapping data, as is often the case in practice (e.g., customer bases of different companies). Based on the intuition that values present in different columns related by a schema matching will have similar "semantic type", and that this can be captured using distributions over values ("statistical types"), we develop a method for validating 1-1 and compositional schema matchings. Our technique is based on three key technical ideas. First, we propose a generic measure for comparing two …

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K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay Apr 2008

K-Sketch: A 'Kinetic' Sketch Pad For Novice Animators, Richard C. Davis, Brien Colwell, James A. Landay

Research Collection School Of Computing and Information Systems

Because most animation tools are complex and timeconsuming to learn and use, most animations today are created by experts. To help novices create a wide range of animations quickly, we have developed a general-purpos informal, 2D animation sketching system called K-Sketch. Field studies investigating the needs of animatorsnd would-be animators helped us collect a library of usage scenarios for our tool. A novel optimization technique enabled us to design an interface that is simultaneously fast, simple, and powerful. The result is a pen-based system that relies on users’ intuitive sense of space and time while still supporting a wide range …

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Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha Apr 2008

Rate-Diversity And Resource-Aware Broadcast And Multicast In Multi-Rate Wireless Mesh Networks, Bao Hua Liu, Chun Tung Chou, Archan Misra, Sanjay Jha

Research Collection School Of Computing and Information Systems

This paper focuses on the problem of increasing the traffic capacity (volume of admissible traffic) of broadcast and multicast flows in a wireless mesh network (WMN). We study and suggest routing strategies where the process of constructing the forwarding tree considers three distinct features: (a) the ability of individual mesh nodes to perform link-layer broadcasts at multiple rates, (b) the wireless broadcast advantage, whereby a single broadcast transmission covers multiple neighboring receivers and (c) the residual transmission capacity at a WMN node, subject to intereference-based constraints from existing traffic flows in its neighborhood. Our metric of interest is the total …

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Measurement And Estimation Of Network Qos Among Peer Xbox 360 Game Players, Youngki Lee, Sharad Agarwal, Chris Butcher, Jitu Padhye Apr 2008

Measurement And Estimation Of Network Qos Among Peer Xbox 360 Game Players, Youngki Lee, Sharad Agarwal, Chris Butcher, Jitu Padhye

Research Collection School Of Computing and Information Systems

The research community has proposed several techniques for estimating the quality of network paths in terms of delay and capacity. However, few techniques have been studied in the context of large deployed applications. Network gaming is an application that is extremely sensitive to network path quality [1,2,3]. Yet, the quality of network paths among players of large, wide-area games and techniques for estimating it have not received much attention from the research community.

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E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan Apr 2008

E-Government Implementation: A Macro Analysis Of Singapore's E-Government Initiatives, Calvin M.L. Chan, Yi Meng Lau, Shan L. Pan

Research Collection School Of Computing and Information Systems

This paper offers a macro perspective of the various activities involved in the implementation of e-government through an interpretive analysis of the various e-government-related initiatives undertaken by the Singapore Government. The analysis lead to the identification of four main components in the implementation of e-government, namely (i) information content, (ii) ICT infrastructure, (iii) e-government infostructure, and (iv) e-government promotion. These four components were then conceptually integrated into the e-Government Implementation Framework. This paper suggests that this framework can either be used as a descriptive tool to organize and coordinate various e-government initiatives, or be used as a prescriptive structure to …

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Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo Apr 2008

Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo

Research Collection School Of Computing and Information Systems

Optimistic fair exchange is a kind of protocols to solve the problem of fair exchange between two parties. Almost all the previous work on this topic are provably secure only in the random oracle model. In PKC 2007, Dodis et al. considered optimistic fair exchange in a multi-user setting, and showed that the security of an optimistic fair exchange in a single-user setting may no longer be secure in a multi-user setting. Besides, they also proposed one and reviewed several previous construction paradigms and showed that they are secure in the multi-user setting. However, their proofs are either in the …

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Comp-Ref: A Technique To Guide The Delegation Of Responsibilities To Components In Software Systems, Subhajit Datta, Robert Van Engelen Apr 2008

Comp-Ref: A Technique To Guide The Delegation Of Responsibilities To Components In Software Systems, Subhajit Datta, Robert Van Engelen

Research Collection School Of Computing and Information Systems

In software systems, components collaborate to collectively fulfill requirements. A key concern of software design is the delegation of responsibilities to components such that user needs are most expediently met. This paper presents the COMP-REF technique based on a set of metrics and Linear Programming (LP) to guide the allocation of responsibilities of a system’s components. We define the metrics Aptitude Index, Requirement Set, and Concordance Index to extract some design characteristics and use these metrics in an optimization algorithm. Results from experimental validation of the COMP-REF technique across a range of software systems are reported. We also …

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Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng Mar 2008

Processing Transitive Nearest-Neighbor Queries In Multi-Channel Access Environments, Xiao Zhang, Wang-Chien Lee, Prasnjit Mitra, Baihua Zheng

Research Collection School Of Computing and Information Systems

Wireless broadcast is an efficient way for information dissemination due to its good scalability [10]. Existing works typically assume mobile devices, such as cell phones and PDAs, can access only one channel at a time. In this paper, we consider a scenario of near future where a mobile device has the ability to process queries using information simultaneously received from multiple channels. We focus on the query processing of the transitive nearest neighbor (TNN) search [19]. Two TNN algorithms developed for a single broadcast channel environment are adapted to our new broadcast enviroment. Based on the obtained insights, we propose …

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Harmoni: Context-Aware Filtering Of Sensor Data For Continuous Remote Health Monitoring, Iqbal Mohomed, Archan Misra, Maria Ebling, William Jerome Mar 2008

Harmoni: Context-Aware Filtering Of Sensor Data For Continuous Remote Health Monitoring, Iqbal Mohomed, Archan Misra, Maria Ebling, William Jerome

Research Collection School Of Computing and Information Systems

A promising architecture for remote healthcare monitoring involves the use of a pervasive device (such as a cellular phone), which aggregates data from multiple body-worn medical sensors and transmits the data to the backend. Unfortunately, the volume of data generated by increasingly sophisticated continuouslyactive sensors can overwhelm the resources on the mobile device. We propose imbuing the mobile device with the intelligence to perform context-aware filtering of sensor data streams in order to reduce transmissions in cases where the observed data corresponds to the norm expected by the system in a given context. To investigate the efficacy of this technique, …

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On-Line Discovery Of Hot Motion Paths, Dimitris Sacharidis, Kostas Patroumpas, Manolis Terrovitis, Verena Kantere, Michalis Potamias, Kyriakos Mouratidis, Timos Sellis Mar 2008

On-Line Discovery Of Hot Motion Paths, Dimitris Sacharidis, Kostas Patroumpas, Manolis Terrovitis, Verena Kantere, Michalis Potamias, Kyriakos Mouratidis, Timos Sellis

Research Collection School Of Computing and Information Systems

We consider an environment of numerous moving objects, equipped with location-sensing devices and capable of communicating with a central coordinator. In this setting, we investigate the problem of maintaining hot motion paths, i.e., routes frequently followed by multiple objects over the recent past. Motion paths approximate portions of objects' movement within a tolerance margin that depends on the uncertainty inherent in positional measurements. Discovery of hot motion paths is important to applications requiring classification/profiling based on monitored movement patterns, such as targeted advertising, resource allocation, etc. To achieve this goal, we delegate part of the path extraction process to objects, …

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Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao Feb 2008

Integrating Temporal Difference Methods And Self‐Organizing Neural Networks For Reinforcement Learning With Delayed Evaluative Feedback, Ah-Hwee Tan, Ning Lu, Dan Xiao

Research Collection School Of Computing and Information Systems

This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the …

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Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann Feb 2008

Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann

Research Collection School Of Computing and Information Systems

Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …

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On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang Feb 2008

On Ranking Controversies In Wikipedia: Models And Evaluation, Ba-Quy Vuong, Ee Peng Lim, Aixin Sun, Minh-Tam Le, Hady Wirawan Lauw, Kuiyu Chang

Research Collection School Of Computing and Information Systems

Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with controversial content. They also occur frequently among contributors who are "aggressive" or controversial in their personalities. In this paper, we aim to identify controversial articles in Wikipedia. We propose three models, namely the Basic model and two Controversy Rank (CR) models. These models draw clues from collaboration and edit history instead of interpreting the actual articles or edited content. While …

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Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan Jan 2008

Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

The use of a team of weak learners to learn a dataset has been shown better than the use of one single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be one of the best off-the-shelf classifiers. However, some problems still remain, including determining the optimal number of weak learners and the overfitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of genetic algorithm, weak learner and pattern distributor. In this paper, …

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Benford And Your Taxes, Manoj Thulasidas Jan 2008

Benford And Your Taxes, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

Nothing is certain but death and taxes, they say. On the death front, we are making some inroads with all our medical marvels, at least in postponing it if not actually avoiding it. But when it comes to taxes, we have no defense other than a bit of creativity in our tax returns.

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Probabilistic Sales Forecasting For Small And Medium-Size Business Operations, Randall E. Duran Jan 2008

Probabilistic Sales Forecasting For Small And Medium-Size Business Operations, Randall E. Duran

Research Collection School Of Computing and Information Systems

One of the most important aspects of operating a business is the forecasting of sales and allocation of resources to fulfill sales. Sales assessments are usually based on mental models that are not well defined, may be biased, and are difficult to refine and improve over time. Defining sales forecasting models for small- and medium-size business operations is especially difficult when the number of sales events is small but the revenue per sales event is large. This chapter reviews the challenges of sales forecasting in this environment and describes how incomplete and potentially suspect information can be used to produce …

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Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song Jan 2008

Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song

Research Collection School Of Computing and Information Systems

Classical multi-echelon repairable item inventory models are based either on steady-state analysis or infinite repair capacity, which may not work well in situations when the demand is nonstationary, or repair capacity is limited. In this paper, we propose an analytical model for evaluating system performance that works well under limited repair capacity and nonstationary demands. Following the METRIC methodology, we then develop an optimisation algorithm to solve the corrective maintenance problem in military logistics. Experimental results show that our approach yields good solutions efficiently. This work has also resulted in a software that has been field-tested by a military organisation.

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Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna Jan 2008

Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this chapter, we study the problem of selecting documents so as to extract terrorist event information from a collection of documents. We represent an event by its entity and relation instances. Very often, these entity and relation instances have to be extracted from multiple documents. We therefore define an information extraction (IE) task as selecting documents and extracting from which entity and relation instances relevant to a user-specified event (aka domain specific event entity and relation extraction). We adopt domain specific IE patterns to extract potentially relevant entity and relation instances from documents, and develop a number of document …

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The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao Jan 2008

The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao

Research Collection School Of Computing and Information Systems

In this work, we liken the solving of combinatorial optimization problems under a prescribed computational budget as hunting for oil in an unexplored ground. Using this generic model, we instantiate an iterative deepening genetic annealing (IDGA) algorithm, which is a variant of memetic algorithms. Computational results on the traveling salesman problem show that IDGA is more effective than standard genetic algorithms or simulated annealing algorithms or a straightforward hybrid of them. Our model is readily applicable to solve other combinatorial optimization problems.

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A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang Jan 2008

A Growth-Theoretic Empirical Analysis Of Simultaneity In Cross-National E-Commerce Development, Shu-Chun Ho, Robert J. Kauffman, Ting-Peng Liang

Research Collection School Of Computing and Information Systems

The emergence of information and communication technologies infrastructure has transformed the global economy. The development of information technology infrastructure is limited to some developed countries though. This research explores the role of information technology infrastructure in B2C e-commerce growth at the country-level from the perspective of growth theory in economics. We propose a hybrid exogenous and endogenous growth model to explain e-commerce growth. We estimate a panel data model that incorporates the direct effects of e-commerce infrastructure and other key explanatory variables. We further specify a simultaneous effects model that permits the analysis of reverse causality in the association between …

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Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky Jan 2008

Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

In this report, we present overview and comparative analysis of our HLF detection system, which achieves the top performance among all type-A submissions in 2008. We also describe preliminary evaluation of our video search system, CuZero, in the interactive search task.

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Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Jan 2008

Face Annotation Using Transductive Kernel Fisher Discriminant, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Face annotation in images and videos enjoys many potential applications in multimedia information retrieval. Face annotation usually requires many training data labeled by hand in order to build effective classifiers. This is particularly challenging when annotating faces on large-scale collections of media data, in which huge labeling efforts would be very expensive. As a result, traditional supervised face annotation methods often suffer from insufficient training data. To attack this challenge, in this paper, we propose a novel Transductive Kernel Fisher Discriminant (TKFD) scheme for face annotation, which outperforms traditional supervised annotation methods with few training data. The main idea of …

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Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky Jan 2008

Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

No abstract provided.

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Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston Jan 2008

Collective Outsourcing To Market (Com): A Market-Based Framework For Information Supply Chain Outsourcing, Fang Fang, Zhiling Guo, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other …

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Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang Jan 2008

Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang

Research Collection School Of Computing and Information Systems

Searchable encryption schemes allow users to perform keyword based searches on an encrypted database. Almost all existing such schemes only consider the scenario where a single user acts as both the data owner and the querier. However, most databases in practice do not just serve one user; instead, they support search and write operations by multiple users. In this paper, we systematically study searchable encryption in a practical multi-user setting. Our results include a set of security notions for multi-user searchable encryption as well as a construction which is provably secure under the newly introduced security notions.

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Location Update Versus Paging Trade-Off In Cellular Networks: An Approach Based On Vector Quantization, Abhishek Roy, Archan Misra, Sajal K. Das Dec 2007

Location Update Versus Paging Trade-Off In Cellular Networks: An Approach Based On Vector Quantization, Abhishek Roy, Archan Misra, Sajal K. Das

Research Collection School Of Computing and Information Systems

In this paper we propose two information-theoretic techniques for efficiently trading off the location update and paging costs associated with mobility management in wireless cellular networks. Previous approaches attempt to always accurately convey a mobile's movement sequence and hence, cannot reduce the signaling cost below the entropy bound. Our proposed techniques, however, exploit rate-distortion theory to arbitrarily reduce the update cost, at the expense of an increase in the corresponding paging overhead. To this end, we describe two location tracking algorithms, based on spatial quantization and temporal quantization, which first quantize the movement sequence into a smaller set of codewords, …

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Study Of The Minimum Spanning Hyper-Tree Routing Algorithm In Wireless Sensor Networks, Ting Yang, Yugeng Sun, Zhaoxia Wang, Juwei Zhang, Yingqiang Ding Dec 2007

Study Of The Minimum Spanning Hyper-Tree Routing Algorithm In Wireless Sensor Networks, Ting Yang, Yugeng Sun, Zhaoxia Wang, Juwei Zhang, Yingqiang Ding

Research Collection School Of Computing and Information Systems

Designing energy-efficient routing protocols to effectively increase the networks' lifetime and provide the robust network service is one of the important problems in the research of wireless sensor networks. Using the hyper-graph theory, the paper represents large-scale wireless sensor networks into a hyper-graph model, which can effectively decrease the control messages in routing process. Based on this mathematic model, the paper presents the minimum spanning hyper-tree routing algorithm in synchronous wireless sensor networks (MSHT-SN), which builds a minimum energy consumption tree for data collection from multi-nodes to Sink node. The validity of the algorithm is proved by the theatrical analysis. …

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Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan Dec 2007

Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

This letter proposes to use multiorder neurons for clustering irregularly shaped data arrangements. Multiorder neurons are an evolutionary extension of the use of higher-order neurons in clustering. Higher-order neurons parametrically model complex neuron shapes by replacing the classic synaptic weight by higher-order tensors. The multiorder neuron goes one step further and eliminates two problems associated with higher-order neurons. First, it uses evolutionary algorithms to select the best neuron order for a given problem. Second, it obtains more information about the underlying data distribution by identifying the correct order for a given cluster of patterns. Empirically we observed that when the …

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