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Computer Engineering

2009

Articles 1 - 15 of 15

Full-Text Articles in Databases and Information Systems

Coherent Phrase Model For Efficient Image Near-Duplicate Retrieval, Yiqun Hu, Xiangang Cheng, Liang-Tien Chia, Xing Xie, Deepu Rajan, Ah-Hwee Tan Dec 2009

Coherent Phrase Model For Efficient Image Near-Duplicate Retrieval, Yiqun Hu, Xiangang Cheng, Liang-Tien Chia, Xing Xie, Deepu Rajan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper presents an efficient and effective solution for retrieving image near-duplicate (IND) from image database. We introduce the coherent phrase model which incorporates the coherency of local regions to reduce the quantization error of the bag-of-words (BoW) model. In this model, local regions are characterized by visual phrase of multiple descriptors instead of visual word of single descriptor. We propose two types of visual phrase to encode the coherency in feature and spatial domain, respectively. The proposed model reduces the number of false matches by using this coherency and generates sparse representations of images. Compared to other method, the …

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A Robust Damage Assessment Model For Corrupted Database Systems, Ge Fu, Hong Zhu, Yingjiu Li Dec 2009

A Robust Damage Assessment Model For Corrupted Database Systems, Ge Fu, Hong Zhu, Yingjiu Li

Research Collection School Of Computing and Information Systems

An intrusion tolerant database uses damage assessment techniques to detect damage propagation scales in a corrupted database system. Traditional damage assessment approaches in a intrusion tolerant database system can only locate damages which are caused by reading corrupted data. In fact, there are many other damage spreading patterns that have not been considered in traditional damage assessment model. In this paper, we systematically analyze inter-transaction dependency relationships that have been neglected in the previous research and propose four different dependency relationships between transactions which may cause damage propagation. We extend existing damage assessment model based on the four novel dependency …

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Scalable Detection Of Partial Near-Duplicate Videos By Visual-Temporal Consistency, Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-Seng Chua Oct 2009

Scalable Detection Of Partial Near-Duplicate Videos By Visual-Temporal Consistency, Hung-Khoon Tan, Chong-Wah Ngo, Richang Hong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Following the exponential growth of social media, there now exist huge repositories of videos online. Among the huge volumes of videos, there exist large numbers of near-duplicate videos. Most existing techniques either focus on the fast retrieval of full copies or near-duplicates, or consider localization in a heuristic manner. This paper considers the scalable detection and localization of partial near-duplicate videos by jointly considering visual similarity and temporal consistency. Temporal constraints are embedded into a network structure as directed edges. Through the structure, partial alignment is novelly converted into a network flow problem where highly efficient solutions exist. To precisely …

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Mining Globally Distributed Frequent Subgraphs In A Single Labeled Graph, Xing Jiang, Hui Xiong, Chen Wang, Ah-Hwee Tan Oct 2009

Mining Globally Distributed Frequent Subgraphs In A Single Labeled Graph, Xing Jiang, Hui Xiong, Chen Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Recent years have observed increasing efforts on graph mining and many algorithms have been developed for this purpose. However, most of the existing algorithms are designed for discovering frequent subgraphs in a set of labeled graphs only. Also, the few algorithms that find frequent subgraphs in a single labeled graph typically identify subgraphs appearing regionally in the input graph. In contrast, for real-world applications, it is commonly required that the identified frequent subgraphs in a single labeled graph should also be globally distributed. This paper thus fills this crucial void by proposing a new measure, termed G-Measure, to find globally …

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Analyzing The Video Popularity Characteristics Of Large-Scale User Generated Content Systems, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue Moon Oct 2009

Analyzing The Video Popularity Characteristics Of Large-Scale User Generated Content Systems, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue Moon

Research Collection School Of Computing and Information Systems

User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show …

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Semantics-Preserving Bag-Of-Words Models For Efficient Image Annotation, Lei Wu, Steven C. H. Hoi, Nenghai Yu Oct 2009

Semantics-Preserving Bag-Of-Words Models For Efficient Image Annotation, Lei Wu, Steven C. H. Hoi, Nenghai Yu

Research Collection School Of Computing and Information Systems

The Bag-of-Words (BoW) model is a promising image representation for annotation. One critical limitation of existing BoW models is the semantic loss during the codebook generation process, in which BoW simply clusters visual words in Euclidian space. However, distance between two visual words in Euclidean space does not necessarily reflect the semantic distance between the two concepts, due to the semantic gap between low-level features and high-level semantics. In this paper, we propose a novel scheme for learning a codebook such that semantically related features will be mapped to the same visual word. In particular, we consider the distance between …

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Distribution-Based Concept Selection For Concept-Based Video Retrieval, Juan Cao, Hongfang Jing, Chong-Wah Ngo, Yongdong Zhang Oct 2009

Distribution-Based Concept Selection For Concept-Based Video Retrieval, Juan Cao, Hongfang Jing, Chong-Wah Ngo, Yongdong Zhang

Research Collection School Of Computing and Information Systems

Query-to-concept mapping plays one of the keys to concept-based video retrieval. Conventional approaches try to find concepts that are likely to co-occur in the relevant shots from the lexical or statistical aspects. However, the high probability of co-occurrence alone cannot ensure its effectiveness to distinguish the relevant shots from the irrelevant ones. In this paper, we propose distribution-based concept selection (DBCS) for query-to-concept mapping by analyzing concept score distributions of within and between relevant and irrelevant sets. In view of the imbalance between relevant and irrelevant examples, two variants of DBCS are proposed respectively by considering the two-sided and onesided …

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Temporal Data Classification Using Linear Classifiers, Peter Revesz, Thomas Triplet Sep 2009

Temporal Data Classification Using Linear Classifiers, Peter Revesz, Thomas Triplet

CSE Conference and Workshop Papers

Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that describes measurements over a period of time in history while the predicted class is expected to occur in the future. We describe a new temporal classification method that improves the accuracy of standard classification methods. The benefits of the method are tested on weather forecasting using the meteorological database from the Texas Commission on Environmental Quality.

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Self-Authentication Of Audio Signals By Chirp Coding, Jonathan Blackledge, Eugene Coyle Sep 2009

Self-Authentication Of Audio Signals By Chirp Coding, Jonathan Blackledge, Eugene Coyle

Conference papers

This paper discusses a new approach to ‘watermarking’ digital signals using linear frequency modulated or ‘chirp’ coding. The principles underlying this approach are based on the use of a matched filter to provide a reconstruction of a chirped code that is uniquely robust in the case of signals with very low signal-to-noise ratios. Chirp coding for authenticating data is generic in the sense that it can be used for a range of data types and applications (the authentication of speech and audio signals, for example). The theoretical and computational aspects of the matched filter and the properties of a chirp …

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Wireless Networks: Spert: A Stateless Protocol For Energy-Sensitive Real-Time Routing For Wireless Sensor Network, Sohail Jabbar, Abid Ali Minhas, Raja Adeel Akhtar Aug 2009

Wireless Networks: Spert: A Stateless Protocol For Energy-Sensitive Real-Time Routing For Wireless Sensor Network, Sohail Jabbar, Abid Ali Minhas, Raja Adeel Akhtar

International Conference on Information and Communication Technologies

Putting constraints on performance of a system in the temporal domain, some times turns right into wrong and update into outdate. These are the scenarios where apposite value of time inveterate in the reality. But such timing precision not only requires tightly scheduled performance constraints but also requires optimal design and operation of all system components. Any malfunctioning at any relevant aspect may causes a serious disaster and even loss of human lives. Managing and interacting with such real-time system becomes much intricate when the resources are limited as in wireless sensor nodes. A wireless sensor node is typically comprises …

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Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan Jul 2009

Learning And Inferencing In User Ontology For Personalized Semantic Web Search, Xing Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of …

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Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan Feb 2009

Learning Image‐Text Associations, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Web information fusion can be defined as the problem of collating and tracking information related to specific topics on the World Wide Web. Whereas most existing work on Web information fusion has focused on text-based multidocument summarization, this paper concerns the topic of image and text association, a cornerstone of cross-media Web information fusion. Specifically, we present two learning methods for discovering the underlying associations between images and texts based on small training data sets. The first method based on vague transformation measures the information similarity between the visual features and the textual features through a set of predefined domain-specific …

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A Mobile Ecg Monitoring System With Context Collection, Jin Peng Li, Damon Berry, Richard Hayes Jan 2009

A Mobile Ecg Monitoring System With Context Collection, Jin Peng Li, Damon Berry, Richard Hayes

Conference Papers

Preventative health management represents a shift from the traditional approach of reactive treatment-based healthcare towards a proactive wellness-management approach where patients are encouraged to stay healthy with expert support when they need it, at any location and any time. This work represents a step along the road towards proactive, preventative healthcare for cardiac patients. It seeks to develop a smart mobile ECG monitoring system that requests and records context information about what is happening around the subject when an arrhythmia event occurs. Context information about the subject’s activities of daily living will, it is hoped, provide an enriched data set …

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Archetype Alignment: A Two-Level Driven Semantic Matching Approach To Interoperability In The Clinical Domain, Damon Berry, Jesus Bisbal Jan 2009

Archetype Alignment: A Two-Level Driven Semantic Matching Approach To Interoperability In The Clinical Domain, Damon Berry, Jesus Bisbal

Conference Papers

Semantic interoperability between electronic health record systems and other information systems in the health domain implies agreement about the structure and the meaning of the information that is communicated. There are still a number of similar but different EHR system approaches. Some of the newer approaches adopt the two-layer model approach where a generic reference model is constrained by archetypes into valid clinical concepts which can be exchanged. The meaning of the concepts that are represented by an archetype can be conveyed by embedding codes from a commonly recognised terminology at appropriate points in the archetype. However, as the number …

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Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan Jan 2009

Modelling Situation Awareness For Context‐Aware Decision Support, Yu-Hong Feng, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Situation awareness modelling is popularly used in the command and control domain for situation assessment and decision support. However, situation models in real-world applications are typically complex and not easy to use. This paper presents a Context-aware Decision Support (CaDS) system, which consists of a situation model for shared situation awareness modelling and a group of entity agents, one for each individual user, for focused and customized decision support. By incorporating a rule-based inference engine, the entity agents provide functions including event classification, action recommendation, and proactive decision making. The implementation and the performance of the proposed system are demonstrated …

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