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Articles 6571 - 6600 of 7453

Full-Text Articles in Physical Sciences and Mathematics

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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Innovation Stack - Choosing Innovations For Commercialization, Arcot Desai Narasimhalu Aug 2007

Innovation Stack - Choosing Innovations For Commercialization, Arcot Desai Narasimhalu

Research Collection School Of Computing and Information Systems

This paper describes a method for enterprises to order the innovations of interest according to a number of parameters including their own business strategy and core competencies. The method takes into account aspects such as ability to create entry barriers and complementary assets. Enterprises can now use this method to both filter out innovations that may not be of interest to them and then order the short listed or selected innovations according to their attractiveness.

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Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang Aug 2007

Cost-Time Sensitive Decision Tree With Missing Values, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang

Research Collection School Of Computing and Information Systems

Cost-sensitive decision tree learning is very important and popular in machine learning and data mining community. There are many literatures focusing on misclassification cost and test cost at present. In real world application, however, the issue of time-sensitive should be considered in cost-sensitive learning. In this paper, we regard the cost of time-sensitive in cost-sensitive learning as waiting cost (referred to WC), a novelty splitting criterion is proposed for constructing cost-time sensitive (denoted as CTS) decision tree for maximal decrease the intangible cost. And then, a hybrid test strategy that combines the sequential test with the batch test strategies is …

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Re-Engineering Xid Technologies - From Enterprise To Consumer Markets, Arcot Desai Narasimhalu Aug 2007

Re-Engineering Xid Technologies - From Enterprise To Consumer Markets, Arcot Desai Narasimhalu

Research Collection School Of Computing and Information Systems

Several studies have addressed the process of taking ideas to markets but few have shared the experiences of start up companies that have reexamined their product strategies and repositioned their products and services for better revenues and profits. This paper reports the efforts related to repositioning of XID technologies, a start up company, into new markets while continuing to exploit its core technical competencies.

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Enhanced Security By Os-Oriented Encapsulation In Tpm-Enabled Drm, Yongdong Wu, Feng Bao, Robert H. Deng, Marc Mouffron, Frederic Rousseau Aug 2007

Enhanced Security By Os-Oriented Encapsulation In Tpm-Enabled Drm, Yongdong Wu, Feng Bao, Robert H. Deng, Marc Mouffron, Frederic Rousseau

Research Collection School Of Computing and Information Systems

The Trusted Computing Group (TCG) defines the specifications for the Trusted Platform Module (TPM) and corresponding trust mechanisms that allow a TPM-enabled platform to run only authenticated software. For example, the operating system (OS) can use the facilities provided by the TPM to authenticate a Digital Rights Management (DRM) application before allowing it to run. However TCG does not provide any clear specification on what kind of software can be regarded as trusted and hence be authenticated. In fact it is unlikely that there will be a clear line between the software that should be authenticated and those should not, …

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Century: Automated Aspects Of Patient Care, Marion Blount, John Davis, Maria Ebling, Ji Hyun Kim, Kyun Hyun Kim, Kang Yoon Lee, Archan Misra, Se Hun Park, Daby Sow, Young Ju Tak, Min Wang, Karen Witting Aug 2007

Century: Automated Aspects Of Patient Care, Marion Blount, John Davis, Maria Ebling, Ji Hyun Kim, Kyun Hyun Kim, Kang Yoon Lee, Archan Misra, Se Hun Park, Daby Sow, Young Ju Tak, Min Wang, Karen Witting

Research Collection School Of Computing and Information Systems

Remote health monitoring affords the possibility of improving the quality of health care by enabling relatively inexpensive out-patient care. However, remote health monitoring raises new a problem: the potential for data explosion in health care systems. To address this problem, the remote health monitoring systems must be integrated with analysis tools that provide automated trend analysis and event detection in real time. In this paper, we propose an overview of Century, an extensible framework for analysis of large numbers of remote sensor-based medical data streams.

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A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan Aug 2007

A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan

Research Collection School Of Computing and Information Systems

Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group …

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Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu Aug 2007

Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu

Research Collection School Of Computing and Information Systems

This paper introduces an additional feature to the strategy canvas and value curve that will make innovation designers more effective. The new feature is to let the innovators carry out the designs of their new innovations taking into account both the cost of improving the quality of a parameter that the users value highly and the savings accrued from the drop in provisioning for parameters that users place less emphasis in an innovation.

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An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair Aug 2007

An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair

Research Collection School Of Computing and Information Systems

Grammar checking and correction comprise of the primary problems in the area of Natural Language Processing (NLP). Traditional approaches fall into two major categories: Rule based and Corpus based. While the former relies heavily on grammar rules the latter approach is statistical in nature. We provide a novel corpus based approach for grammar checking that uses the principles of an Artificial Immune System (AIS).We treat grammatical error as pathogens (in immunological terms) and build antibody detectors capable of detecting grammatical errors while allowing correct constructs to filter through. Our results show that it is possible to detect a range of …

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Are You Too Smart For Your Own Good?, M. Thulasidas Aug 2007

Are You Too Smart For Your Own Good?, M. Thulasidas

Research Collection School Of Computing and Information Systems

Knowledge can be a bad thing, if others are taking credit for it. TECHNICAL knowledge is not always a good thing for you in the modern workplace.

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Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang Jul 2007

Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang

Research Collection School Of Computing and Information Systems

Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word …

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Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo Jul 2007

Improving Memory-Based Collaborative Filtering Using A Factor-Based Approach, Zhenxue Zhang, Dongsong Zhang, Zhiling Guo

Research Collection School Of Computing and Information Systems

Collaborative Filtering (CF) systems generate recommendations for a user by aggregating item ratings of other like-minded users. The memory-based approach is a common technique used in CF. This approach first uses statistical methods such as Pearson’s Correlation Coefficient to measure user similarities based on their previous ratings on different items. Users will then be grouped into different neighborhood depending on the calculated similarities. Finally, the system will generate predictions on how a user would rate a specific item by aggregating ratings on the item cast by the identified neighbors of his/her. However, current memory-based CF method only measures user similarities …

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An Empirical Study On Large-Scale Content-Based Image Retrieval, Yuk Man Wong, Steven C. H. Hoi, Michael R. Lyu Jul 2007

An Empirical Study On Large-Scale Content-Based Image Retrieval, Yuk Man Wong, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems. In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building Web-scale …

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Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Jul 2007

Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Acquisition of context poses unique challenges to mobile context-aware recommender systems. The limited resources in these systems make minimizing their context acquisition a practical need, and the uncertainty in the mobile environment makes missing and erroneous context inputs a major concern. In this paper, we propose an approach based on Bayesian networks (BNs) for building recommender systems that minimize context acquisition. Our learning approach iteratively trims the BN-based context model until it contains only the minimal set of context parameters that are important to a user. In addition, we show that a two-tiered context model can effectively capture the causal …

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The Business Model Of "Software-As-A-Service", Dan Ma Jul 2007

The Business Model Of "Software-As-A-Service", Dan Ma

Research Collection School Of Computing and Information Systems

The emergence of the software-as-a-service (SaaS) business model has attracted great attentions from both researchers and practitioners. SaaS vendors deliver on-demand information processing services to users, and thus offer computing utility rather than the standalone software itself. In this work, the author propose an analytical model to study the competition between the SaaS and the traditional COTS (commercial off-the-shelf) solutions for software applications. The author show that when software applications become open, modulated, and standardized, the SaaS business model will take a significant market share. In addition, under certain market conditions, offering users an easy exit option through the software …

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Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo Jul 2007

Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the …

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Appraisal - Who Needs It?, M. Thulasidas Jul 2007

Appraisal - Who Needs It?, M. Thulasidas

Research Collection School Of Computing and Information Systems

WE GO through this ordeal every year when our boss- es appraise our performance. Our career progression, bonus and salary depend on it. So, we spend sleepless nights agonising over it.

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Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Jul 2007

Learning Causal Models For Noisy Biological Data Mining: An Application To Ovarian Cancer Detection, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Undetected errors in the expression measurements from highthroughput DNA microarrays and protein spectroscopy could seriously affect the diagnostic reliability in disease detection. In addition to a high resilience against such errors, diagnostic models need to be more comprehensible so that a deeper understanding of the causal interactions among biological entities like genes and proteins may be possible. In this paper, we introduce a robust knowledge discovery approach that addresses these challenges. First, the causal interactions among the genes and proteins in the noisy expression data are discovered automatically through Bayesian network learning. Then, the diagnosis of a disease based on …

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Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau Jul 2007

Generating Job Schedules For Vessel Operations In A Container Terminal, Thin Yin Leong, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

No abstract provided.

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Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis Jul 2007

Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

In the k-medoid problem, given a dataset P, we are asked to choose kpoints in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarly in this paper, we also aim at approximate solutions. We consider, however, the continuous version of the problem, where the points in P move and our task is to maintain the medoid set on-the-fly …

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On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee Jul 2007

On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee

Research Collection School Of Computing and Information Systems

A continuous nearest neighbor (CNN) search, which retrieves the nearest neighbors corresponding to every point in a given query line segment, is important for location-based services such as vehicular navigation and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server systems but not in the environment of wireless data broadcast, where uplink communication channels from mobile devices to the …

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Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe Jul 2007

Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

The organisational behaviour and management literature has devoted a lot attention on various factors affecting organisational learning. While there has been much work done to examine trust in promoting organisational learning, there is a lack of consensus on the specific type of trust involved. The purpose of this paper is to highlight the importance of interpersonal trust in promoting organisational learning and propose a research agenda to test the extent of interpersonal trust on organisational learning. This paper contributes to the existing organisational learning literature by specifying a specific form of trust, interpersonal trust, which promotes organisational learning and proposing …

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