Data Storage Systems Commons^™

Super Special Codes Using Super Matrices, Florentin Smarandache, W.B. Vasantha Kandasamy, K. Ilanthenral

Branch Mathematics and Statistics Faculty and Staff Publications

The new classes of super special codes are constructed in this book using the specially constructed super special vector spaces. These codes mainly use the super matrices. These codes can be realized as a special type of concatenated codes. This book has four chapters. In chapter one basic properties of codes and super matrices are given. A new type of super special vector space is constructed in chapter two of this book. Three new classes of super special codes namely, super special row code, super special column code and super special codes are introduced in chapter three. Applications of these …

An Investigation Of Multiple Integration Techniques For Information Systems: A Model For Integrating Data Warehousing, Erp, And Soa In Practice, Jessie Burns

CCAC Theses and Dissertations

This study addressed issues associated with implementing multiple data integrators. The process included implementing the same data integrator multiple times or implementing multiple different data integrators. It was shown that single data integrators implementations were failing at high rates. Environments were complicated because there were more acquisitions and mergers now than in the past, companies were required to be competitive while implementations were taking place, and possibly had short implementation time frames.

The main goal of this study was to develop an agile, sturdy, and rigorous model that addressed the needs of companies that found themselves in situations where they …

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 …

Semantic Context Transfer Across Heterogeneous Sources For Domain Adaptive Video Search, Yu-Gang Jiang, Chong-Wah Ngo, Shih-Fu Chang

Research Collection School Of Computing and Information Systems

Automatic video search based on semantic concept detectors has recently received significant attention. Since the number of available detectors is much smaller than the size of human vocabulary, one major challenge is to select appropriate detectors to response user queries. In this paper, we propose a novel approach that leverages heterogeneous knowledge sources for domain adaptive video search. First, instead of utilizing WordNet as most existing works, we exploit the context information associated with Flickr images to estimate query-detector similarity. The resulting measurement, named Flickr context similarity (FCS), reflects the co-occurrence statistics of words in image context rather than textual …

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 …

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 …

Towards Google Challenge: Combining Contextual And Social Information For Web Video Categorization, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Web video categorization is a fundamental task for web video search. In this paper, we explore the Google challenge from a new perspective by combing contextual and social information under the scenario of social web. The semantic meaning of text (title and tags), video relevance from related videos, and user interest induced from user videos, are integrated to robustly determine the video category. Experiments on YouTube videos demonstrate the effectiveness of the proposed solution. The performance reaches 60% improvement compared to the traditional text based classifiers.

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 …

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 …

Large-Scale Near-Duplicate Web Video Search: Challenge And Opportunity, Wan-Lei Zhao, Song Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The massive amount of near-duplicate and duplicate web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of …

Exploring Inter-Concept Relationship With Context Space For Semantic Video Indexing, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Semantic concept detectors are often individually and independently developed. Using peripherally related concepts for leveraging the power of joint detection, which is referred to as context-based concept fusion (CBCF), has been one of the focus studies in recent years. This paper proposes the construction of a context space and the exploration of the space for CBCF. Context space considers the global consistency of concept relationship, addresses the problem of missing annotation, and is extensible for cross-domain contextual fusion. The space is linear and can be built by modeling the inter-concept relationship through annotation provided by either manual labeling or machine …

A Video Manager, Nicholas Omann

Honors Capstones

Capstone submitted as a graduate requirement for the BSU Honors Program.

Visual Word Proximity And Linguistics For Semantic Video Indexing And Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Bag-of-visual-words (BoW) has recently become a popular representation to describe video and image content. Most existing approaches, nevertheless, neglect inter-word relatedness and measure similarity by bin-to-bin comparison of visual words in histograms. In this paper, we explore the linguistic and ontological aspects of visual words for video analysis. Two approaches, soft-weighting and constraint-based earth mover’s distance (CEMD), are proposed to model different aspects of visual word linguistics and proximity. In soft-weighting, visual words are cleverly weighted such that the linguistic meaning of words is taken into account for bin-to-bin histogram comparison. In CEMD, a cross-bin matching algorithm is formulated such …

Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …

Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.

Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu

Research Collection School Of Computing and Information Systems

In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …

Bag-Of-Visual-Words Expansion Using Visual Relatedness For Video Indexing, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.

Multimodal News Story Clustering With Pairwise Visual Near-Duplicate Constraint, Xiao Wu, Chong-Wah Ngo, Alexander G. Hauptmann

Research Collection School Of Computing and Information Systems

Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit clusters of varying densities, shapes, and sizes. Traditional algorithms are found to be ineffective in mining these types of clusters. This paper offers a new perspective by exploring the pairwise visual cues deriving from near-duplicate keyframes (NDK) for constraint-based clustering. We propose a constraint-driven co-clustering algorithm (CCC), which utilizes the near-duplicate constraints built on top of text, to mine topic-related stories and the outliers. With CCC, the duality between stories and their underlying …

Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

No abstract provided.

Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

In this report, we present overview and comparative analysis of our HLF detection system, which achieves the top performance among all type-A submissions in 2008. We also describe preliminary evaluation of our video search system, CuZero, in the interactive search task.

Back-Up Server For Computer Science Department, Victoria Gaylord

Mahurin Honors College Capstone Experience/Thesis Projects

Because Western Kentucky University does not maintain a back-up system for its departments, the Computer Science Department has implemented its own. Using Bacula software on a Unix server, files from faculty desktop computers and servers are backed up to a tape drive on a daily basis. The server is protected from outside threats with a carefully configured firewall script. This paper explains how both the firewall and the back-up software were implemented and how successful that implementation has been.

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 …

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 …

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 …

Sheep Updates 2007 - Part 4, Dean Thomas, Dominique Blache, Dean Revell, Hayley Norman, Phil Vercoe, Zoey Durmic, Serina Digby, Di Mayberry, Megan Chadwick, Martin Sillence, David Masters, R. Silberstein, F. Byrne, P. G. H. Nichols, J. Young, L. Aitkins, M. G. Wilmot, A. J. Rintoul, T. Lambert, D. R. Mcclements, P. Raper, P. Ward, C. Walton, T. York, David Pethick, David Hopkins, Malcolm Mcphee, D. B. Savage, J. V. Nolan, I. R. Godwin, A. Aoetpah, T. Nguyen, N. Baillie, C. Lawler, Ken Geenty, John Smith, Darryl Smith, Tim Dyall, Grant Uphill, John Young, Michael Paton, John Dorrian

Sheep Updates

This session covers eight papers from different authors:

GRAZING

1. The impact of high dietary salt and its implications for the management of livestock grazing saline land, Dean Thomas, Dominique Blache, Dean Revell, Hayley Norman, Phil Vercoe, Zoey Durmic, Serina Digby, Di Mayberry, Megan Chadwick, Martin Sillence and David Masters, CRC for Plant-based Management of Dryland Salinity, Faculty of Natural & Agricultural Sciences, The University of Western Australia, WA.

2. Sustainable Grazing on Saline Lands - outcomes from the WA1 research project, H.C. Norman^1,2, D.G. Masters^1,2, R. Silberstein^1,2, F. Byrne^2,3, P.G.H. Nichols …

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 …

Web-Based Library For Student Projects/Theses And Faculty Research Papers, Rudy Senjaya

Theses Digitization Project

The purpose of this project is to make available a Web-based Library, a web application developed for the Department of Computer Science at CSUSB to manage student projects/theses and faculty papers. The project is designed in accordance with Model-View-Controller (MVC) design pattern using the Jakarta Struts framework and iBATIS Data Mapper framework from Apache Software Foundation, JavaServer Pages (JSP), and MySQL database.

Modeling Local Interest Points For Semantic Detection And Video Search At Trecvid 2006, Yu-Gang Jiang, Xiaoyong Wei, Chong-Wah Ngo, Hung-Khoon Tan, Wanlei Zhao, Xiao Wu

Research Collection School Of Computing and Information Systems

Local interest points (LIPs) and their features have been shown to obtain surprisingly good results in object detection and recognition. Its effectiveness and scalability, however, have not been seriously addressed in large-scale multimedia database, for instance TRECVID benchmark. The goal of our works is to investigate the role and performance of LIPs, when coupling with multi-modality features, for high-level feature extraction and automatic video search.

An Operational Model For Mobile Sensor Cloud Management, Indrajeet Kalyankar

Electrical & Computer Engineering Theses & Dissertations

Mobile sensors provide a safe, cost effective method for gathering information in hazardous environments. When the hazardous environment is either unexplored, such as the surface of Mars, or unanticipated, such as the result of chemical contamination, it is desirable for a system to gather information with a minimal amount of outside control (localization, decision control, etc.) and prepositioned sensors. If one takes a look at the number of the sensors deployed on a scale, at the lower end is the sole, multipurpose sensor unit. The upper end deals with hordes of inexpensive, expendable sensors. In the middle, a cluster of …

Threading And Autodocumenting News Videos: A Promising Solution To Rapidly Browse News Topics, Xiao Wu, Chong-Wah Ngo, Qing Li

Research Collection School Of Computing and Information Systems

This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary