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Research Collection School Of Computing and Information Systems

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Articles 6031 - 6060 of 6891

Full-Text Articles in Physical Sciences and Mathematics

Option-Based Risk Management: A Field Study Of Sequential Information Technology Investment Decisions, Michel Benaroch, Mark Jeffery, Robert John Kauffman, Sandeep Shah Oct 2007

Option-Based Risk Management: A Field Study Of Sequential Information Technology Investment Decisions, Michel Benaroch, Mark Jeffery, Robert John Kauffman, Sandeep Shah

Research Collection School Of Computing and Information Systems

This field study research evaluates the viability of applying an option-based risk management (OBRiM) framework, and its accompanying theoretical perspective and methodology, to real-world sequential information technology (IT) investment problems. These problems involve alternative investment structures that bear different risk profiles for the firm, and also may improve the payoffs of the associated projects and the organization's performance. We sought to surface the costs, benefits, and risks associated with a complex sequential investment setting that has the key features that OBRiM treats. We combine traditional, purchased real options that subsequently create strategic flexibility for the decision maker, with implicit or …

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Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu Oct 2007

Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu

Research Collection School Of Computing and Information Systems

We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. The "breakdown" is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call strands. We developed efficient algorithms to quickly mine out all strands by iterative growth. In the "build-up" stage, these strands are grouped up to form the support sets from which all approximate patterns would be identified. A salient feature of our algorithm is its ability to grow the frequent patterns by iteratively …

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Performance Of Network-Coding In Multi-Rate Wireless Environments For Multicast Applications, Luiz F. M. Viera, Archan Misra, Mario Gerla Oct 2007

Performance Of Network-Coding In Multi-Rate Wireless Environments For Multicast Applications, Luiz F. M. Viera, Archan Misra, Mario Gerla

Research Collection School Of Computing and Information Systems

This paper investigates the interaction between net-work coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. We …

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Npake+: A Hierarchical Group Password-Authenticated Key Exchange Protocol Using Different Passwords, Zhiguo Wan, Robert H. Deng, Feng Bao, Bart Preneel Oct 2007

Npake+: A Hierarchical Group Password-Authenticated Key Exchange Protocol Using Different Passwords, Zhiguo Wan, Robert H. Deng, Feng Bao, Bart Preneel

Research Collection School Of Computing and Information Systems

Although two-party password-authenticated key exchange (PAKE) protocols have been intensively studied in recent years, group PAKE protocols have received little attention. In this paper, we propose a hierarchical group PAKE protocol nPAKE+ protocol under the setting where each party shares an independent password with a trusted server. The nPAKE+ protocol is a novel combination of the hierarchical key tree structure and the password-based Diffie-Hellman exchange, and hence it achieves substantial gain in computation efficiency. In particular, the computation cost for each client in our protocol is only O(logn). Additionally, the hierarchical feature of nPAKE+ enables every subgroup obtains their own …

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Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao Oct 2007

Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph is constructed to model the color similarity between two shots. Then OM based on Kuhn-Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and bipartite graph construction based on …

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Analyzing Service Usage Patterns: Methodology And Simulation, Qianhui (Althea) Liang, Jen-Yao Chung Oct 2007

Analyzing Service Usage Patterns: Methodology And Simulation, Qianhui (Althea) Liang, Jen-Yao Chung

Research Collection School Of Computing and Information Systems

This paper proposes that service mining technology will power the construction of new business services via both intra- and inter-enterprise service assembly within the Service Oriented Architecture (SOA) framework. We investigate the methodologies of service mining at the component level of service usage. We also demonstrate how mining of service usage patterns is intended to be used to improve different aspects of service composition. Simulation experiments conducted for mining at the component level are analyzed. The processing details within a general service mining deployment are demonstrated.

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Flexible Access Control To Jpeg 2000 Image Code-Streams, Yongdong Wu, Di Ma, Robert H. Deng Oct 2007

Flexible Access Control To Jpeg 2000 Image Code-Streams, Yongdong Wu, Di Ma, Robert H. Deng

Research Collection School Of Computing and Information Systems

JPEG 2000 is an international standard for still image compression in the 21st century. Part 8 of the standard, named JPSEC, is concerned with all the security aspects, in particular to access control and authentication. This paper presents a novel access control scheme for JPEG 2000 image code-streams. The proposed scheme is secure against collusion attacks and highly efficient. The scheme is also very flexible, allowing access control to JPEG 2000 image code-streams according to any combination of resolution, quality layer and region of interest. The "encrypt once, decrypt many ways" property of our scheme is designed to work seamlessly …

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A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim Oct 2007

A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.

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I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon Oct 2007

I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon

Research Collection School Of Computing and Information Systems

User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with …

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Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo Sep 2007

Evaluating Bag-Of-Visual-Words Representations In Scene Classification, Jun Yang, Yu-Gang Jiang, Alexander G. Hauptmann, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Based on keypoints extracted as salient image patches, an image can be described as a “bag of visual words” and this representation has been used in scene classification. The choice of dimension, selection, and weighting of visual words in this representation is crucial to the classification performance but has not been thoroughly studied in previous work. Given the analogy between this representation and the bag-of-words representation of text documents, we apply techniques used in text categorization, including term weighting, stop word removal, feature selection, to generate image representations that differ in the dimension, selection, and weighting of visual words. The …

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Anonymous And Authenticated Key Exchange For Roaming Networks, Guomin Yang, Duncan S. Wong, Xiaotie Deng Sep 2007

Anonymous And Authenticated Key Exchange For Roaming Networks, Guomin Yang, Duncan S. Wong, Xiaotie Deng

Research Collection School Of Computing and Information Systems

User privacy is a notable security issue in wireless communications. It concerns about user identities from being exposed and user movements and whereabouts from being tracked. The concern of user privacy is particularly signified in systems which support roaming when users are able to hop across networks administered by different operators. In this paper, we propose a novel construction approach of anonymous and authenticated key exchange protocols for a roaming user and a visiting server to establish a random session key in such a way that the visiting server authenticates the user's home server without knowing exactly who the user …

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Overview Of The Imageclef 2007 Object Retrieval Task, Thomas Deselaers, Steven C. H. Hoi Sep 2007

Overview Of The Imageclef 2007 Object Retrieval Task, Thomas Deselaers, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved. Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods …

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Evolutionary Combinatorial Optimization For Recursive Supervised Learning With Clustering, Kiruthika Ramanathan, Sheng Uei Guan Sep 2007

Evolutionary Combinatorial Optimization For Recursive Supervised Learning With Clustering, Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

The idea of using a team of weak learners to learn a dataset is a successful one in literature. In this paper, we explore a recursive incremental approach to ensemble learning. In this paper, patterns are clustered according to the output space of the problem, i.e., natural clusters are formed based on patterns belonging to each class. A combinatorial optimization problem is therefore formed, which is solved using evolutionary algorithms. The evolutionary algorithms identify the "easy" and the "difficult" clusters in the system. The removal of the easy patterns then gives way to the focused learning of the more complicated …

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Who’S Creating?, M. Thulasidas Sep 2007

Who’S Creating?, M. Thulasidas

Research Collection School Of Computing and Information Systems

We don’t read to retain information or knowledge any more. We search, scan, locate keywords, browse and bookmark. The Internet is doing to our reading habits what the calculator did to our arithmetic abilities. Knowledge is not cheap, although our easy access to it through the Internet may indicate otherwise. When we all become users of information, our knowledge will stop at its current level because nobody will be creating it any more.

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Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo Sep 2007

Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

An overwhelming volume of news videos from different channels and languages is available today, which demands automatic management of this abundant information. To effectively search, retrieve, browse and track cross-lingual news stories, a news story similarity measure plays a critical role in assessing the novelty and redundancy among them. In this paper, we explore the novelty and redundancy detection with visual duplicates and speech transcripts for cross-lingual news stories. News stories are represented by a sequence of keyframes in the visual track and a set of words extracted from speech transcript in the audio track. A major difference to pure …

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Cross-Language And Cross-Media Image Retrieval: An Empirical Study At Imageclef2007, Steven C. H. Hoi Sep 2007

Cross-Language And Cross-Media Image Retrieval: An Empirical Study At Imageclef2007, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

This paper summarizes our empirical study of cross-language and cross-media image retrieval at the CLEF image retrieval track (ImageCLEF2007). In this year, we participated in the ImageCLEF photo retrieval task, in which the goal of the retrieval task is to search natural photos by some query with both textual and visual information. In this paper, we study the empirical evaluations of our solutions for the image retrieval tasks in three aspects. First of all, we study the application of language models and smoothing strategies for text-based image retrieval, particularly addressing the short text query issue. Secondly, we study the cross-media …

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Taking Stock Of The Creative Commons Experiment: Monitoring The Use Of Creative Commons Licenses And Evaluating Its Implications For The Future Of Creative Commons And For Copyright Law, Giorgos Cheliotis, Kam Wai, Warren Bartholomew Chik, Ankit Guglani, Giri Kumar Tayi Sep 2007

Taking Stock Of The Creative Commons Experiment: Monitoring The Use Of Creative Commons Licenses And Evaluating Its Implications For The Future Of Creative Commons And For Copyright Law, Giorgos Cheliotis, Kam Wai, Warren Bartholomew Chik, Ankit Guglani, Giri Kumar Tayi

Research Collection School Of Computing and Information Systems

We provide an analysis of the use of Creative Commons (CC) licenses, an approach to licensing creative works which has become very popular among authors who wish to promote more liberal sharing and use of their work. We provide data demonstrating the popularity of CC, examine which specific license types within the CC framework are most popular, and then identify contributing factors for the relative popularity of some of the license types.

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Column Heterogeneity As A Measure Of Data Quality, Bing Tian Dai, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubramanian Sep 2007

Column Heterogeneity As A Measure Of Data Quality, Bing Tian Dai, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubramanian

Research Collection School Of Computing and Information Systems

Data quality is a serious concern in every data management application, and a variety of quality measures have been proposed, including accuracy, freshness and completeness, to capture the common sources of data quality degradation. We identify and focus attention on a novel measure, column heterogeneity, that seeks to quantify the data quality problems that can arise when merging data from different sources. We identify desiderata that a column heterogeneity measure should intuitively satisfy, and discuss a promising direction of research to quantify database column heterogeneity based on using a novel combination of cluster entropy and soft clustering. Finally, we present …

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Globally Distributed Software Development Project Performance: An Empirical Analysis, Narayanasamy Ramasubbu, Rajesh Krishna Balan Sep 2007

Globally Distributed Software Development Project Performance: An Empirical Analysis, Narayanasamy Ramasubbu, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Software firms are increasingly distributing their software development effort across multiple locations. In this paper we present the results of a two year field study that investigated the effects of dispersion on the productivity and quality of distributed software development. We first develop a model of distributed software development. We then use the model, along with our empirically observed data, to understand the consequences of dispersion on software project performance. Our analysis reveals that, even in high process maturity environments, a) dispersion significantly reduces development productivity and has effects on conformance quality, and b) these negative effects of dispersion can …

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Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou Sep 2007

Robust Local Search And Its Application To Generating Robust Schedules, Hoong Chuin Lau, Fei Xiao, Thomas Ou

Research Collection School Of Computing and Information Systems

In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from scenario-based or stochastic programming approaches often used to tackle uncertainty. Given a value 0 < ? 1, we are interested to know what the robust objective value is, i.e. the optimal value if we allow an chance of not meeting it, assuming that certain data values are defined on bounded random variables. We show how a standard local search or metaheuristic routine can be extended to efficiently construct a decision rule with such guarantee, albeit heuristically. We demonstrate its practical applicability on the Resource Constrained Project Scheduling Problem with minimal and maximal time lags (RCPSP/max) taking into consideration activity duration uncertainty. Experiments show that, partial order schedules can be constructed that are robust in our sense without the need for a large planned horizon (due date), which improves upon the work proposed by Policella et al. 2004.

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Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo Sep 2007

Rushes Video Summarization By Object And Event Understanding, Feng Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recognition. Our system is composed of two major steps. First, based on video structuring, we filter undesirable shots and minimize the inter-shot redundancy by repetitive shot detection. Second, a representability measure is proposed to model the presence of objects and four audio-visual events: motion activity of objects, camera motion, scene changes, and speech content, in a video clip. The video …

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Ntu: Solution For The Object Retrieval Task Of The Imageclef2007, Steven C. H. Hoi Sep 2007

Ntu: Solution For The Object Retrieval Task Of The Imageclef2007, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Object retrieval is an interdisciplinary research problem between object recognition and content-based image retrieval (CBIR). It is commonly expected that object retrieval can be solved more effectively with the joint maximization of CBIR and object recognition techniques. We study a typical CBIR solution with application to the object retrieval tasks [26,27]. We expect that the empirical study in this work will serve as a baseline for future research when using CBIR techniques for object recognition.

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Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo Sep 2007

Practical Elimination Of Near-Duplicates From Web Video Search, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Current web video search results rely exclusively on text keywords or user-supplied tags. A search on typical popular video often returns many duplicate and near-duplicate videos in the top results. This paper outlines ways to cluster and filter out the nearduplicate video using a hierarchical approach. Initial triage is performed using fast signatures derived from color histograms. Only when a video cannot be clearly classified as novel or nearduplicate using global signatures, we apply a more expensive local feature based near-duplicate detection which provides very accurate duplicate analysis through more costly computation. The results of 24 queries in a data …

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Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo Sep 2007

Ontology-Enriched Semantic Space For Video Search, Xiao-Yong Wei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for …

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Context-Based Detection Of Clone-Related Bugs, Lingxiao Jiang, Zhendong Su, Edwin Chiu Sep 2007

Context-Based Detection Of Clone-Related Bugs, Lingxiao Jiang, Zhendong Su, Edwin Chiu

Research Collection School Of Computing and Information Systems

Studies show that programs contain much similar code, commonly known as clones. One of the main reasons for introducing clones is programmers' tendency to copy and paste code to quickly duplicate functionality. We commonly believe that clones can make programs difficult to maintain and introduce subtle bugs. Although much research has proposed techniques for detecting and removing clones to improve software maintainability, little has considered how to detect latent bugs introduced by clones. In this paper, we introduce a general notion of context-based inconsistencies among clones and develop an efficient algorithm to detect such inconsistencies for locating bugs. We have …

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Difference Computation Of Large Models, Christoph Treude, Stefan Berlik, Sven Wenzel, Udo Kelter Sep 2007

Difference Computation Of Large Models, Christoph Treude, Stefan Berlik, Sven Wenzel, Udo Kelter

Research Collection School Of Computing and Information Systems

Modern software engineering practices lead to large models which exist in many versions. Version management systems should offer a service to compare, and possibly merge, these models. The computation of a difference between large models is a big challenge; current algorithms are too inefficient here. We present a new technique for computing differences between models. In practical tests, this technique has been an order of magnitude faster than currently known algorithms. The main idea is to use a high-dimensional search tree for efficiently finding similar model elements. Individual elements are mapped onto a vector of numerical values using a collection …

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Realizing Live Sequence Charts In System Verilog, Hai H. Wang, Shengchao Qin, Jun Sun, Jin Song Dong Aug 2007

Realizing Live Sequence Charts In System Verilog, Hai H. Wang, Shengchao Qin, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

The design of an embedded control system starts with an investigation of properties and behaviors of the process evolving within its environment, and an analysis of the requirement for its safety performance. In early stages, system requirements are often specied as scenarios of behavior using sequence charts for different use cases. This specication must be precise, intuitive and expressive enough to capture different aspects of embedded control systems. As a rather rich and useful extension to the classical message sequence charts, Live Sequence Charts (LSC), which provide a rich collection of constructs for specifying both possible and mandatory behaviors, are …

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Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng Aug 2007

Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng

Research Collection School Of Computing and Information Systems

Coronary artery disease (CAD) is a main cause of death in the world. Finding cost-effective methods to predict CAD is a major challenge in public health. In this paper, we investigate the combined effects of genetic polymorphisms and non-genetic factors on predicting the risk of CAD by applying well known classification methods, such as Bayesian networks, naïve Bayes, support vector machine, k-nearest neighbor, neural networks and decision trees. Our experiments show that all these classifiers are comparable in terms of accuracy, while Bayesian networks have the additional advantage of being able to provide insights into the relationships among the variables. …

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Near-Duplicate Keyframe Identification With Interest Point Matching And Pattern Learning, Wan-Lei Zhao, Chong-Wah Ngo, Hung-Khoon Tan, Xiao Wu Aug 2007

Near-Duplicate Keyframe Identification With Interest Point Matching And Pattern Learning, Wan-Lei Zhao, Chong-Wah Ngo, Hung-Khoon Tan, Xiao Wu

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for near-duplicate keyframe (NDK) identification by matching, filtering and learning of local interest points (LIPs) with PCA-SIFT descriptors. The issues in matching reliability, filtering efficiency and learning flexibility are novelly exploited to delve into the potential of LIP-based retrieval and detection. In matching, we propose a one-to-one symmetric matching (OOS) algorithm which is found to be highly reliable for NDK identification, due to its capability in excluding false LIP matches compared with other matching strategies. For rapid filtering, we address two issues: speed efficiency and search effectiveness, to support OOS with a new index …

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Mapping Better Business Strategies With Gis, Tin Seong Kam Aug 2007

Mapping Better Business Strategies With Gis, Tin Seong Kam

Research Collection School Of Computing and Information Systems

The value of location as a business measure is fast becoming an important consideration for organisations. GIS (Geographical Information Systems), with its capability to manage, display, analyse business information spatially, is emerging as a powerful location intelligence tool. In the US, Starbucks, Blockbuster, Hyundai, and thousands of other businesses use census data and GIS software to help them understand what types of people buy their products and services, and how to better market to these consumers. For example, McDonald’s in Japan uses a GIS system to overlay demographic information on maps to help identify promising new store sites. Singapore Management …

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