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RESEARCH HIGHLIGHTS

Some of the project highlights of the Department are listed below:

Computational Intelligence Networking and Systems Pattern Recognition and Machine Learning Databases and Information Management Others


Computational Intelligence

A Critiquing System for Enhancing Writing Competency Using Automatic Text Analysis
Staff Dr. CHEUNG, William Kwok Wai (Project Investigator)
Abstract To build a web supported learning system with an automatic text analysis module in it, so that (1) teachers can monitor and manage individual student’s writing processes, and (2) students can submit drafts during their writing processes and receive just-in-time subtheme suggestions (critiques) from the system.

A Model-based Approach to Distributed Data Mining with Privacy Preservation
Staff Dr. CHEUNG, William Kwok Wai (Supervisor of PhD Student Mr. ZHANG, Xiaofeng)
Abstract To investigate a principled way of learning global statistical models (for clustering and manifold discovery) from physically distributed local data subsets. Research issues include deriving a proper local data abstractions, learning global generative models from the local abstractions, and enabling negotiation among the local data sources for optimizing the global model accuracy with a minimum cost.

Non-negative Matrix Factorization Based Belief Compression and Clustering for Solving POMDPs
Staff Dr. CHEUNG, William Kwok Wai (Supervisor of PhD Student Ms. LI, Xin)
Abstract The main objective of this project is to study how to integrate two approaches, namely belief compression and belief clustering, to address the intractability of POMDP problems. Techniques involved include data clustering, dimension reduction techniques and their integration into a value-directed framework for computing optimal policy for POMDPs.

Privacy Policy Enforcement in Data Analysis Workflows
Staff Dr. CHEUNG, William Kwok Wai (Supervisor of MPhil Student Mr. CHAN, Kai Kin)
Abstract To study a semantic approach for enforcing privacy policies in data analysis workflow systems. In particular, we introduce privacy preservation and analysis-relevant concepts as ontologies, incorporate them into a policy framework which represents polices, resolves potential conflicts among them, enforces them as well as provides suggestions on corrective actions.

Discrete integrable systems and their applications to convergence acceleration algorithms
Staff Dr. TAM, Hon Wah (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~tam/rgc09-10_index.html
Abstract This research includes: (1) studying the integrable bilinear study of the Heisenberg-type equations and their discrete analogues. The emphasis is placed on integrable discretizations of some Heisenberg-type equations such as the Myrzakulov equations. (2) investigating some properties of discrete integrable systems that are related to the properties of convergence acceleration algorithms. We expect that discretizing integrable PDEs will lead to new sequence transformations.

On Motion Based Visual Feature Selections for Lip-Reading
Staff Prof. CHEUNG, Yiu Ming (Project Investigator)
Abstract Lip-reading has potential attractie applications in information security, speech recognition, and so forth. This project is to develop a new visual feature representation and extraction approach to the lip localization for lip-reading. The proposed method features high accuracy of lip localization and robust performance against the shadow. We build up a prototype of lip-reading system.

Associative Indexing for Semantic Visual Information Discovery
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract Current visual information retrieval is concerned with low-level features. The key to effective semantic visual information search critically depends on the indexing mechanism. In this project, we shall develop a methodology for supporting high-level semantic visual information discovery through the creation of associative indexes, which may be automatically built up and expanded by utilizing ontological data relationships and contextual knowledge.

Automatic Generation of High Precision Image Annotations through Concept Propagation
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract An effective mechanism of identifying image contents is semantic annotation. Without effective annotations, the semantic index cannot be built. The objective of this research is to address this problem by establishing algorithms for the automated generation of high-precision semantic image annotations. In doing so, high precision searching of a vast amount of otherwise unsearchable image collections would become possible.

Mining of Semantic Image Content Using Collective Web Intelligence
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract Human users spend a vast amount of time in interacting with image contents on the Web. Their interaction entails the exercise of considerable perceptive intelligence, visual judgment and mental evaluation. In this project, a collaborative indexing mechanism is developed whereby the aggregate intelligence and judgement of different Web users are continuously transferred to the Web.

Semantic Access and Characterisation of Web Images
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract The Web is becoming increasingly image centred. By injecting different levels of semantic characterisation into Web images by purely automatic means, this research will raise the value and utility of the Web, and to allow the discovery and deployment of an important portion of the Web which up to now has not been substantially explored.

Autonomy-Oriented Computing (AOC), Self-Organized Computability, and Complex Data Mining
Staff Prof. LIU, Jiming (Project Investigator)
Abstract Future challenges will lie in breakthroughs in scalable/robust computational solutions to complex data-mining problems that are: (1) Petabyte-scale (e.g., mining social networks), (2) dynamically-evolving (e.g., detecting social norms), (3) interaction-rich as well as trans-disciplinary (e.g., preventing economic/ecological crisis), and (4) highly-distributed (e.g., community evolution). This project concerns the development of an unconventional computing paradigm, called Autonomy-Oriented Computing (AOC).

Complex Emergent Behavior, Self-Organized Criticality, and Phase Transition in Multi-Agent Systems
Staff Prof. LIU, Jiming (Supervisor of MPhil Student Mr. HU, Bingcheng)
Abstract In this project, we address several issues on modeling complex or emergent behaviors in Multi-Agent Systems. In particular, we focus on the local-global relationship in a Self-Organizing Multi-Agent System (or SOMAS), a RoboNBA system, and study the phenomena of self-organized criticality (SOC) and phase transition in SOMAS.

Mechanism Design for Multi-Agent Systems in Distributed Data Mining
Staff Prof. LIU, Jiming (Project Investigator)
Abstract Methods for governing competitive systems have been studied in the field of distributed artificial intelligence (DAI), e.g., for autonomous agents and multi-agent systems. Mechanism design theories have been proposed and applied to networking and agent-based e-commerce. In this project, we are interested in investigating the use and impacts of mechanism design in distributed data-mining (DDM).


Networking and Systems

A General Approach for Fast Extraction of Low-level Disk Characteristics
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract The performance gap between magnetic disks and RAM is steadily increasing. In order to bridge this gap, it is valuable to obtain and exploit accurate information about the low-level disk characteristics so as to optimize the system performance. In this project, we investigate the low-level disk characteristics and develop tools that can efficiently extract variant low-level disk characteristics.

A Microeconomic Approach for Digital Rights Management in P2P Networks
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract Peer-to-peer (P2P) networks are self-organizing distributed systems, with no centralized authority or infrastructure. In this project, we propose novel approaches to both new and existing problems, and unify them into one integrated approach for enhancing the copyright protection in P2P networks and thwarting selfish behaviors.

Efficient Resource Management in Reliable Wavelength-Routed WDM Networks
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract Optical networks based on wavelength-division multiplexing (WDM) are growing at unprecedented rates to accommodate the ever-increasing demand for bandwidth. The objective of this project is to develop an efficient resource management scheme for reliable wavelength-routed WDM networks. This includes an advanced routing and wavelength assignment (RWA) algorithm with restoration capability, and also an effective wavelength converter allocation scheme.

Explore Business Models for Streaming Applications in Peer-to-Peer Environments
Staff Dr. CHU, Xiao Wen (Co-Investigator of External Project)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract Peer-to-peer (P2P) file-sharing systems have already become one of the most efficient tools for individuals to exchange digital information goods over Internet. The project involves in designing incentive mechanisms, investigating possible business models and pricing schemes that work for P2P streaming applications. These issues are all critical for the success of P2P streaming applications.

Lightpath Rerouting in Wavelength-Routed WDM Networks
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract WDM technology has been widely deployed in optical backbone networks to accommodate the ever-increasing bandwidth demand. This project aims at decreasing the blocking probability by lightpath rerouting. The first step is to thoroughly investigate the design of intentional lightpath rerouting algorithms, and the second step is to investigate the effect of integrating passive lightpath rerouting and intentional lightpath rerouting.

Performance Evaluation of IEEE 802.11 Based Wireless LAN with Internal UDP Traffic
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract IEEE 802.11 based Wireless LANs have become ubiquitous. The objective of this research project is to design systematic and reproducible experiments to show that, with uncontrolled UDP traffic in the network, the AP will become the system bottleneck and the system goodput could drop to an unacceptable level, mainly due to buffer overflow at the AP.

Using Fuzzy Control Approach to Provide QoS Guarantees in Web Servers
Staff Dr. CHU, Xiao Wen (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~chxw/projects.html
Abstract With the wide spread usage of web applications, the number of accesses to a website is ever increasing. This project aims to address the delay performance problem in two web server architectures: the single-tier architecture and the cluster architecture. We shall investigate ways to manage the resources of the web servers to provide the performance guarantee for premium class users.

Privacy and Security for Advanced Information Systems and Applications
Staff Dr. HU, Haibo (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~haibo/projects.htm
Abstract Privacy and security are two critical concerns in modern advanced information systems, such as mobile information systems and social networking services. This project studies query processing with mutual privacy protection. In outsourced databases, the protection of both data privacy and query privacy are equally important. We design both secure multiparty computation and privacy homomorphism-based techniques for efficient query processing.

Maximizing Lifetime of Sensor-Target Surveillance in Wireless Sensor Networks
Staff Dr. LIU, Hai (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~hliu/
Abstract The proposed research studies the maximal lifetime problem in sensor-target surveillance networks. We will design an optimal schedule for sensor-target surveillance. We will further investigate the dynamic schedule if sensors fail before energy depletion due to unexpected reasons. Finally, we will develop an integrated solution.

Minimum Latency of Aggregation and Gathering in Multihop Wireless Networks with Multiple Radios and Multiple Channels
Staff Dr. LIU, Hai (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~hliu/
Abstract Advance of technologies makes it feasible to equip a wireless node with multiple radios which operate on multiple channels. This research aims to conduct algorithmic studies of minimizing the communication latency by utilizing multiple radios and channels. We focus on the communication schedules for broadcasting, gathering, aggregation and beaconing, under both the protocol interference model and the SINR model.

Movement Control Algorithm for Bi-Connectivity in Robotic Sensor Networks
Staff Dr. LIU, Hai (Project Investigator)
URL http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05555924
Abstract Robots autonomously move to the desired locations based on only 1-hop information, such that the initial and possibly disconnected network is self-organized into a bi-connected network. The objective is to maximize the coverage of the network while minimizing the moving distance of the robots.

QoS-Concerned Rendezvous in Cognitive Radio Networks
Staff Dr. LIU, Hai (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~hliu/
Abstract Rendezvous is a fundamental operation of Cognitive radio network (CRN) in which two or more users meet and establish a communication link on a commonly-available channel, so that consequent information exchange and data communication can be carried on. This research aims at designing rendezvous algorithms for rendezvous on the high-quality channel in finite time.

Rendezvous Algorithm for Cognitive Radio Networks
Staff Dr. LIU, Hai (Project Investigator)
URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5935066&tag=1
Abstract Design algorithms for blind rendezvous (rendezvous without using any centralized controller and common control channel), such that users can simultaneously hop on a commonly-available channel and thus the rendezvous is achieved.

Sensor Placement and Scheduling to Maximize the Lifetime of Wireless Sensor Networks
Staff Dr. LIU, Hai (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~hliu/
Abstract In sensor-target surveillance networks, sensors are placed to watch targets, collect information and forward the data to the base station (BS). The proposed research studies the maximal lifetime problem which is to place and schedule sensors to watch targets in turn, and find routes to pass data to the BS, such that the lifetime of the network is maximized.

Data-Centric Filter Management and Routing Optimization for Distributed Monitoring Systems
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/defacto.html
Abstract This research project proposes to take data-centric designs to improve performance for distributed monitoring systems. Two issues namely filter management for approximate monitoring and routing optimization for in-network data aggregation are studied under this project.

Energy-Conserving Quality-Aware Data Collection in Wireless Sensor Networks
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/ecoquad.html
Abstract Energy efficiency is a critical consideration in the design of a wireless sensor network. This project exploits the trade-off between data quality and communication cost to improve energy efficiency in sensor data collection.

Assignment of Movies to Heterogeneous Video Server
Staff Prof. LEUNG, Yiu Wing (Supervisor of PhD Student Mr. HOU, Yuen Tan Ricky)
URL http://www.comp.hkbu.edu.hk/v1/proj/82/
Abstract As a VOD system is being used and evolved, its servers probably become heterogeneous. We formulate the problem of assigning movies to heterogeneous servers for minimal blocking probability, prove its NP-hardness, and propose to use problem relaxation and goal to get close-to-optimal assignment.

Logical Subnetting for Constructing All-Optical Multi-Fiber Networks
Staff Prof. LEUNG, Yiu Wing (Supervisor of PhD Student Mr. CHAN, Kam Chau Tony)
URL http://www.comp.hkbu.edu.hk/v1/proj/81/
Abstract All-optical multi-fiber networks require large and expensive optical switches. To tackle this problem, the existing approach adopts an individual node perspective and focuses on designing the internal node architectures that require smaller optical switches. In this PhD project, we advocate to take an entire network perspective and propose a logical subnetting approach to further reduce the switch size required.

A Research Centre for Ubiquitous Computing
Staff Prof. NG, Joseph Kee Yin (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~RCUC/
Abstract The objectives of this Research Center are: to coordinate research activities & to excel in some focused areas related to ubiquitous computing; to construct test-beds for testing & benchmarking; and to develop software for ubiquitous applications. The Center will play a leading role in technology transfer and the commercialization of research results to products and services to the consumers.


Pattern Recognition and Machine Learning

Dimensional Reduction and Model Selection in High-dimensional Data Clustering Analysis with Applications
Staff Prof. CHEUNG, Yiu Ming (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~ymc/project/RGC_Visit_Yr11/Project_by_ymc.pdf
Abstract This project is to develop a single learning paradigm for three major tasks in high-dimensional data clustering analysis: (1) Dimensional Reduction, (2) Model Selection, and (3) Model Parameter Estimation. In this approach, both of the feature relevance and the cluster structure are considered. Extensive experiments show the efficacy of the proposed approach.

On Feature Selection in Gaussian Mixture Clustering
Staff Prof. CHEUNG, Yiu Ming (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~ymc/project/Feature_Selection/project.htm
Abstract This project proposes a new method for feature selection in Gaussian mixture clustering, and integrates it with our recently proposed RPEM algorithm so that the three closely-related issues: data clustering, model selection, and the feature selection, are all performed in a single learning process, but not a separated way. Empirical studies have shown the efficacy of the proposed approach.

On Motion Based Visual Feature Selections for Lip-Reading
Staff Prof. CHEUNG, Yiu Ming (Project Investigator)
Abstract Lip-reading has potential attractie applications in information security, speech recognition, and so forth. This project is to develop a new visual feature representation and extraction approach to the lip localization for lip-reading. The proposed method features high accuracy of lip localization and robust performance against the shadow. We build up a prototype of lip-reading system.

Face Template Security
Staff Prof. YUEN, Pong Chi (Supervisor of PhD Student Mr. FENG, Yi Cheng)
URL http://www.comp.hkbu.edu.hk/~ycfeng/project/project.html
Abstract Security and privacy concern is one of the most important issues in biometric recognition systems. Since there are intra-class variations existing in biometric templates, the traditional encryption methods which are sensitive to variations are not available to protect biometric data. Our project goal is to develop reliable face template protecting schemes, which has high security, reliable accuray and cancelability.

Human Behavior Recognition
Staff Prof. YUEN, Pong Chi (Supervisor of PhD Student Mr. LIU, Chang)
URL http://www.comp.hkbu.edu.hk/~cliu/project/project.htm
Abstract Human behavior recognition has so many applications such as visual surveillance, human-computer interfaces, content based video retrieval etc. It is a challenging research area because the dynamic human body motions have unlimited underlying representations. Our project goal is to construct discriminative underlying human action representations, make computer be aware of human action and recognize human behaviors in various scenarios effectively and efficiently.


Databases and Information Management

Adaptive Filtering for Efficient Subgraph Isomorphism in Graph Databases
Staff Dr. CHOI, Byron Koon Kau (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/af.html
Abstract Graph/Network data model has been a powerful tool to model structures such as social networks, network traffic, biological databases and XML, among others. A typical task on graph data is to retrieve substructures embedded. The current state-of-the-art technique almost always comprise two phases -- the filtering and verification phases. We propose to adjust indexes adaptively, in response to query workloads.

Optimizations for the View Update Problem with Emerging Applications
Staff Dr. CHOI, Byron Koon Kau (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/vu.html
Abstract Materialized views have been important in improving query evaluation performance in databases. Since materialized views are managed as real data, they are subjected to both queries and updates. While queries on materialized views are straightforward, updates on views are not. Materialized views play a crucial role in many emerging applications. These call for an investigation on the view update problem.

Updates of Bisimulation of Graphs
Staff Dr. CHOI, Byron Koon Kau (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~bchoi/project/ub.html
Abstract Updates have been an inseparable part of any bisimulation-based systems. However, updates of bisimulation receive less attention when compared to various applications of bisimulation. Previous theoretical studies on bisimulation report that updates on bisimulation are generally not localized. Hence, a simple update on a graph may result in a recomputation. This necessitates a detailed study on such updates.

Privacy and Security for Advanced Information Systems and Applications
Staff Dr. HU, Haibo (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~haibo/projects.htm
Abstract Privacy and security are two critical concerns in modern advanced information systems, such as mobile information systems and social networking services. This project studies query processing with mutual privacy protection. In outsourced databases, the protection of both data privacy and query privacy are equally important. We design both secure multiparty computation and privacy homomorphism-based techniques for efficient query processing.

Data-Centric Filter Management and Routing Optimization for Distributed Monitoring Systems
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/defacto.html
Abstract This research project proposes to take data-centric designs to improve performance for distributed monitoring systems. Two issues namely filter management for approximate monitoring and routing optimization for in-network data aggregation are studied under this project.

Energy-Conserving Quality-Aware Data Collection in Wireless Sensor Networks
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/ecoquad.html
Abstract Energy efficiency is a critical consideration in the design of a wireless sensor network. This project exploits the trade-off between data quality and communication cost to improve energy efficiency in sensor data collection.

iPDA: Privacy-Preserving Location-based Data Access in Mobile Environments
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/ipda.html
Abstract With a location-aware wireless device, a mobile user can query his/her surroundings (e.g., finding the nearest gas station or all shopping centers within 5 miles) at any place, anytime. This project aims to support such location-based services while protecting users' location privacy.

Query Processing in Flash-Based Storage-Centric Sensor Networks
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/qupos.html
Abstract In this project, we investigate innovative query processing algorithms for flash memory based storage-centric sensor networks. Of particular interest are distributed data management issues under sensor system workload given the unique read/write/erase characteristics of flash memories.

Transaction Management for Flash-based Database Systems
Staff Dr. XU, Jian Liang (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~xujl/research/flash.html
Abstract Owing to their superiority in access latency and energy consumption, flash memory drives have recently become a competitive alternative to magnetic hard disks as secondary storage. In this project, we plan to investigate a number of optimization techniques for transaction management in flash-based database systems by exploiting the characteristics of flash memory drives (e.g., out-of-place updating and partial page programming).

Associative Indexing for Semantic Visual Information Discovery
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract Current visual information retrieval is concerned with low-level features. The key to effective semantic visual information search critically depends on the indexing mechanism. In this project, we shall develop a methodology for supporting high-level semantic visual information discovery through the creation of associative indexes, which may be automatically built up and expanded by utilizing ontological data relationships and contextual knowledge.

Automatic Generation of High Precision Image Annotations through Concept Propagation
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract An effective mechanism of identifying image contents is semantic annotation. Without effective annotations, the semantic index cannot be built. The objective of this research is to address this problem by establishing algorithms for the automated generation of high-precision semantic image annotations. In doing so, high precision searching of a vast amount of otherwise unsearchable image collections would become possible.

Semantic Access and Characterisation of Web Images
Staff Prof. LEUNG, Clement Ho Cheung (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~asmimr
Abstract The Web is becoming increasingly image centred. By injecting different levels of semantic characterisation into Web images by purely automatic means, this research will raise the value and utility of the Web, and to allow the discovery and deployment of an important portion of the Web which up to now has not been substantially explored.


Others

A Research Centre for Ubiquitous Computing
Staff Prof. NG, Joseph Kee Yin (Project Investigator)
URL http://www.comp.hkbu.edu.hk/~RCUC/
Abstract The objectives of this Research Center are: to coordinate research activities & to excel in some focused areas related to ubiquitous computing; to construct test-beds for testing & benchmarking; and to develop software for ubiquitous applications. The Center will play a leading role in technology transfer and the commercialization of research results to products and services to the consumers.

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