Physical Sciences and Mathematics Commons^™

Design Lessons On Access Features In Paper, Yin-Leng Theng, Dion Hoe-Lian Goh, Ming Yin, Eng-Kai Suen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Using Nielsen's Heuristic Evaluation, this paper reports a user study with six usability-trained subjects to evaluate PAPER's access features in assisting users to retrieve information efficiently, part of an on-going design partnership with stakeholders and designers/developers. PAPER (Personalised Adaptive Pathways for Exam Resources) is an improved version evolving from an earlier implementation of GeogDL built upon G-Portal, a geospatial digital library infrastructure. After two initial evaluations with student and teacher design partners, PAPER has evolved into a system containing a new bundle of personalized, interactive services with four modules: mock exam; personal coach (practice and review); trend analysis and performance …

Supporting Field Study With Personalized Project Spaces In A Geographical Digital Library, Ee Peng Lim, Aixin Sun, Zehua Liu, John Hedberg, Chew-Hung Chang, Tiong-Sa Teh, Dion Hoe-Lian Goh, Yin-Leng Theng

Research Collection School Of Computing and Information Systems

Digital libraries have been rather successful in supporting learning activities by providing learners with access to information and knowledge. However, this level of support is passive to learners and interactive and collaborative learning cannot be easily achieved. In this paper, we study how digital libraries could be extended to serve a more active role in collaborative learning activities. We focus on developing new services to support a common type of learning activity, field study, in a geospatial context. We propose the concept of personal project space that allows individuals to work in their personalized environment with a mix of private …

High Performance P300 Speller For Brain-Computer Interface, Cuntai Guan, Manoj Thulasidas, Jiankang Wu

Research Collection School Of Computing and Information Systems

P300 speller is a communication tool with which one can input texts or commands to a computer by thought. The amplitude of the P300 evoked potential is inversely proportional to the probability of infrequent or task-related stimulus. In existing P300 spellers, rows and columns of a matrix are intensified successively and randomly, resulting in a stimulus frequency of 1/N (N is the number of rows or columns of the matrix). We propose a new paradigm to display each single character randomly and individually (therefore reducing the stimulus frequency to 1/(N*N)). On-line experiments showed that this new speller significantly improved the …

Method For Identifying Individuals, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

A method and system for identifying a subject comprises obtaining a digitised recording of an electrocardiogram measurement of the subject to be identified, the digitised recording being a cyclic waveform having a peak amplitude. The digitised recording is normalised to reduce variations due to physiological effects, and the normalised recording is processed to determine a feature vector in the frequency domain. The distance between the determined feature vector and a predetermined feature vector is measured to identify the subject.

California State Information Technology Strategic Plan 2004, Office Of The State Chief Information Officer

California Agencies

No abstract provided.

Spatial Queries In Wireless Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Owing to the advent of wireless networking and personal digital devices, information systems in the era of mobile computing are expected to be able to handle a tremendous amount of traffic and service requests from the users. Wireless data broadcast, thanks to its high scalability, is particularly suitable for meeting such a challenge. Indexing techniques have been developed for wireless data broadcast systems in order to conserve the scarce power resources in mobile clients. However, most of the previous studies do not take into account the impact of location information of users. In this paper, we address the issues of …

Accommodating Instance Heterogeneities In Database Integration, Ee Peng Lim, Roger Hsiang-Li Chiang

Research Collection School Of Computing and Information Systems

A complete data integration solution can be viewed as an iterative process that consists of three phases, namely analysis, derivation and evolution. The entire process is similar to a software development process with the target application being the derivation rules for the integrated databases. In many cases, data integration requires several iterations of refining the local-to-global database mapping rules before a stable set of rules can be obtained. In particular, the mapping rules, as well as the data model and query model for the integrated databases have to cope with poor data quality in local databases, ongoing local database updates …

Finding Constrained Frequent Episodes Using Minimal Occurrences, Xi Ma, Hwee Hwa Pang, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Recurrent combinations of events within an event sequence, known as episodes, often reveal useful information. Most of the proposed episode mining algorithms adopt an apriori-like approach that generates candidates and then calculates their support levels. Obviously, such an approach is computationally expensive. Moreover, those algorithms are capable of handling only a limited range of constraints. In this paper, we introduce two mining algorithms - episode prefix tree (EPT) and position pairs set (PPS) - based on a prefix-growth approach to overcome the above limitations. Both algorithms push constraints systematically into the mining process. Performance study shows that the proposed algorithms …

The D-Tree: An Index Structure For Planar Point Queries Location-Based Wireless Services, Jianliang Xu, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Location-based services (LBSs), considered as a killer application in the wireless data market, provide information based on locations specified in the queries. In this paper, we examine the indexing issue for querying location-dependent data in wireless LBSs; in particular, we focus on an important class of queries, planar point queries. To address the issues of responsiveness, energy consumption, and bandwidth contention in wireless communications, an index has to minimize the search time and maintain a small storage overhead. It is shown that the traditional point-location algorithms and spatial index structures fail to achieve either objective or both. This paper proposes …

On Semantic Caching And Query Scheduling For Mobile Nearest-Neighbor Search, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Location-based services have received increasing attention in recent years. In this paper, we address the performance issues of mobile nearest-neighbor search, in which the mobile user issues a query to retrieve stationary service objects nearest to him/her. An index based on Voronoi Diagram is used in the server to support such a search, while a semantic cache is proposed to enhance the access efficiency of the service. Cache replacement policies tailored for the proposed semantic cache are examined. Moreover, several query scheduling policies are proposed to address the inter-cell roaming issues in multi-cell environments. Simulations are conducted to evaluate the …

Blocking Reduction Strategies In Hierarchical Text Classification, Ee Peng Lim, Aixin Sun, Wee-Keong Ng, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

One common approach in hierarchical text classification involves associating classifiers with nodes in the category tree and classifying text documents in a top-down manner. Classification methods using this top-down approach can scale well and cope with changes to the category trees. However, all these methods suffer from blocking which refers to documents wrongly rejected by the classifiers at higher-levels and cannot be passed to the classifiers at lower-levels. We propose a classifier-centric performance measure known as blocking factor to determine the extent of the blocking. Three methods are proposed to address the blocking problem, namely, threshold reduction, restricted voting, and …

A Novel Log-Based Relevance Feedback Technique In Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic gap between low-level features and high-level semantic concepts in CBIR, typical relevance feedback techniques need to perform a lot of rounds of feedback for achieving satisfactory results. These procedures are time-consuming and may make the users bored in the retrieval tasks. For a long-term study purpose in CBIR, we notice that the users' feedback logs can be available and employed for helping the retrieval tasks in CBIR systems. In this paper, we propose a novel …

Improving Transliteration With Precise Alignment Of Phoneme Chunks And Using Contextual Features, Wei Gao, Kam-Fai Wong, Wai Lam

Research Collection School Of Computing and Information Systems

Automatic transliteration of foreign names is basically regarded as a diminutive clone of the machine translation (MT) problem. It thus follows IBM’s conventional MT models under the sourcechannel framework. Nonetheless, some parameters of this model dealing with zero-fertility words in the target sequences, can negatively impact transliteration effectiveness because of the inevitable inverted conditional probability estimation. Instead of source-channel, this paper presents a direct probabilistic transliteration model using contextual features of phonemes with a tailored alignment scheme for phoneme chunks. Experiments demonstrate superior performance over the source-channel for the task of English-Chinese transliteration.

Semantic Web Technology In Support Of Bioinformatics For Glycan Expression, Amit P. Sheth, William S. York, Christopher Thomas, Meenakshi Nagarajan, John A. Miller, Krzysztof Kochut, Satya S. Sahoo, Xiaochuan Yi

Kno.e.sis Publications

Due to the complexity of biological systems, interpretation of data obtained by a single experimental approach can often be interpreted only if viewed from a broader context, taking into account the information obtained by many diverse techniques. The vast amount of interpreted experimental data that is now available via the internet opens the possibility of collecting the relevant pieces of information that will enable scientists to form hypotheses based on the integration of this diverse information. However, the sheer volume of data that is available makes it very difficult to select the information necessary to make a coherent model of …

Lsdis: Large Scale Distributed Information Systems Lab, Amit P. Sheth

Kno.e.sis Publications

The LSDIS (Large Scale Distributed Information Systems) lab was established in 1994 with the guidance and direction provided by Dr. Amit P. Sheth with the help of Dr. John A. Miller and Dr. Krzysztof J. Kochut. In 1998 this faculty group was further strengthened by the addition of Dr. Ismailcem B. Arpinar. LSDIS is the largest research group in Computer Science at UGA and one of the strongest in its area. During Fall 2004, it is funding 15 students (majority of them PhD), and has one research staff.

Over the years LSDIS has been actively involved in research projects in …

Clip-Based Similarity Measure For Hierarchical Video Retrieval, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to the visual and granularity factors. Based on MM and OM, a hierarchical video retrieval framework is constructed for the approximate matching of video clips. To allow the matching between a query and a long video, an online clip segmentation algorithm is also proposed to rapidly locate …

Logic Programs, Iterated Function Systems, And Recurrent Radial Basis Function Networks, Sebastian Bader, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Graphs of the single-step operator for first-order logic programs—displayed in the real plane—exhibit self-similar structures known from topological dynamics, i.e., they appear to be fractals, or more precisely, attractors of iterated function systems. We show that this observation can be made mathematically precise. In particular, we give conditions which ensure that those graphs coincide with attractors of suitably chosen iterated function systems, and conditions which allow the approximation of such graphs by iterated function systems or by fractal interpolation. Since iterated function systems can easily be encoded using recurrent radial basis function networks, we eventually obtain connectionist systems which …

Recommender Systems Research: A Connection-Centric Survey, Saverio Perugini, Marcos André Gonçalves, Edward A. Fox

Computer Science Faculty Publications

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from …

A Spectroscopy Of Texts For Effective Clustering, Wenyuan Li, Wee-Keong Ng, Kok-Leong Ong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

For many clustering algorithms, such as k-means, EM, and CLOPE, there is usually a requirement to set some parameters. Often, these parameters directly or indirectly control the number of clusters to return. In the presence of different data characteristics and analysis contexts, it is often difficult for the user to estimate the number of clusters in the data set. This is especially true in text collections such as Web documents, images or biological data. The fundamental question this paper addresses is: ldquoHow can we effectively estimate the natural number of clusters in a given text collection?rdquo. We propose to use …

Sclope: An Algorithm For Clustering Data Streams Of Categorical Attributes, Kok-Leong Ong, Wenyuan Li, Wee-Keong Ng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorithm based on CLOPE's intuitive observation about cluster histograms. Unlike CLOPE however, our algorithm is very fast and operates within the constraints of a data stream environment. In particular, we designed SCLOPE according to the recent CluStream framework. Our evaluation of SCLOPE shows very promising results. It consistently outperforms CLOPE in speed and scalability tests on our data sets while maintaining high cluster purity; it also supports cluster analysis that other …

Shared-Storage Auction Ensures Data Availability, Hady W. Lauw, Siu-Cheung Hui, Edmund M. K. Lai

Research Collection School Of Computing and Information Systems

Most current e-auction systems are based on the client-server architecture. Such centralized systems provide a single point of failure and control. In contrast, peer-to-peer systems permit distributed control and minimize individual node and link failures' impact on the system. The shared-storage-based auction model described decentralizes services among peers to share the required processing load and aggregates peers' resources for common use. The model is based on the principles of local computation at each peer, direct inter-peer communication, and a shared storage space.

Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li

Research Collection School Of Computing and Information Systems

The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI’s underlying personalisation mechanism. For a quantitative evaluation of the system’s performance, we propose a set of performance indices based on information …

Robust Classification Of Event-Related Potential For Brain-Computer Interface, Manoj Thulasidas

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 …

Sb9: The Ninth Catalogue Of Spectroscopic Binary Orbits, Dimitri Pourbaix, Andrei A. Tokovinin, Alan H. Batten, Francis C. Fekel, William I. Hartkopf, Hugo Levato, Nidia I. Morrell, Guillermo Torres, Stephane Udry

Information Systems and Engineering Management Research Publications

The Ninth Catalogue of Spectroscopic Binary Orbits (http://sb9.astro.ulb.ac.be) continues the series of compilations of spectroscopic orbits carried out over the past 35 years by Batten and collaborators. As of 2004 May 1st, the new Catalogue holds orbits for 2386 systems. Some essential differences between this catalogue and its predecessors are outlined and three straightforward applications are presented: (1) completeness assessment: period distribution of SB1s and SB2s; (2) shortest periods across the H-R diagram; (3) period-eccentricity relation.

Group-Based Relevance Feedback With Support Vector Machine Ensembles, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedback techniquessimply apply the strict binary classifications: positive (relevant) class and negative (irrelevant) class. However, in a real-world relevance feedback task, it is more reasonable and practical to assume the data come from multiple positive classes and one negative class. In order to formulate an effective relevance feedback algorithm, we propose a novel group-based relevance feedback scheme constructed with the SVM ensembles technique. Experiments are conducted to evaluate the performance of our proposed scheme and the traditional …

Gesture Tracking And Recognition For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong

Research Collection School Of Computing and Information Systems

This paper presents a gesture based driven approach for video editing. Given a lecture video, we adopt novel approaches to automatically detect and synchronize its content with electronic slides. The gestures in each synchronized topic (or shot) are then tracked and recognized continuously. By registering shots and slides and recovering their transformation, the regions where the gestures take place can be known. Based on the recognized gestures and their registered positions, the information in slides can be seamlessly extracted, not only to assist video editing, but also to enhance the quality of original lecture video.

Ltam: A Location-Temporal Authorization Model, Hai Yu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

This paper describes an authorization model for specifying access privileges of users who make requests to access a set of locations in a building or more generally a physical or virtual infrastructure. In the model, primitive locations can be grouped into composite locations and the connectivities among locations are represented in a multilevel location graph. Authorizations are defined with temporal constraints on the time to enter and leave a location and constraints on the number of times users can access a location. Access control enforcement is conducted by monitoring user movement and checking access requests against an authorization database. The …

High Accuracy Classification Of Eeg Signal, Wenjie Xu, Cuitai Guan, Chng Eng Siong, S. Ranganatha, Manoj Thulasidas, Jiankang Wu

Research Collection School Of Computing and Information Systems

Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accuracy EEC signal classification method using single trial EEC signal to detect left and right finger movement. We apply an optimal temporal filter to remove irrelevant signal and subsequently extract key features from spatial patterns of EEG signal to perform classification. Specifically, the proposed method transforms the original EEG signal into a spatial pattern and applies the RBF feature selection method to generate robust feature. Classification is performed by the SVM and our experimental result …

Agribusiness Sheep Updates - 2004 Part 3, Ken Hart, Keith Croker, Rob Davidson, Mario D'Antuono, Evan Burt, Tanya Kilminster, Diana Fedorenko, Darryl Mcclements, Robert Beard, Sandy Turton, Martin Atwell, Robert Beard

Sheep Updates

Posters Can Merino Ewes be Teased to Synchronise Oestrus for a Summer/Autumn Mating? Ken Hart, Keith Croker, Department of Agriculture Western Australia, Rob Davidson, School of Animal Biology, University of Western Australia. Mario D'Antuono, Department of Agriculture Western Australia Damara Sheep: Now Looking Domestic Evan Burt and Tanya Kilminster, Department of Agriculture Western Australia Production and Water Use of Lucerne and French Serradella Under Three Sowing Rates Diana Fedorenko1,4, Darryl McClements1,4 , Robert Beard3,4 1Department of Agriculture, 3 Farmer, Meckering, 4CRC for Plant-based Management of Dryland Salinity. E-SHEEP - Individual Animal Management is here Sandy Turton & Martin Atwell, Department …

Enhancing Web Services Description And Discovery To Facilitate Composition, Preeda Rajasekaran, John A. Miller, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

Web services are in the midst of making the transition from being a promising technology to being widely used in the industry. However, most efforts to use Web services have been manual, thus slowing down the ever changing and dynamic businesses of today. In this paper, we contend that more expressive descriptions of Web services will lead to greater automation and thus provide more agility to businesses. We present the METEOR-S front-end tools for source code annotation and semantic Web service description generation. We also present WSDL-S, a language created for incorporating semantic descriptions in the industry wide accepted WSDL, …