Data Storage Systems Commons^™

Entropy And Certainty In Lossless Data Compression, James Jay Jacobs

Dissertations

Data compression is the art of using encoding techniques to represent data symbols using less storage space compared to the original data representation. The encoding process builds a relationship between the entropy of the data and the certainty of the system. The theoretical limits of this relationship are defined by the theory of entropy in information that was proposed by Claude Shannon. Lossless data compression is uniquely tied to entropy theory as the data and the system have a static definition. The static nature of the two requires a mechanism to reduce the entropy without the ability to alter either …

Memory Architecture Template For Fast Block Matching Algorithms On Field Programmable Gate Arrays, Shant Chandrakar

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Fast Block Matching (FBM) algorithms for video compression are well suited for acceleration using parallel data-path architectures on Field Programmable Gate Arrays (FPGAs). However, designing an efficient on-chip memory subsystem to provide the required throughput to this parallel data-path architecture is a complex problem. This thesis presents a memory architecture template that can be parameterized for a given FBM algorithm, number of parallel Processing Elements (PEs), and block size. The template can be parameterized with well known exploration techniques to design efficient on-chip memory subsystems. The memory subsystems are derived for two existing FBM algorithms and are implemented on a …

Self-Healing Cellular Automata To Correct Soft Errors In Defective Embedded Program Memories, Varun Voddi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Static Random Access Memory (SRAM) cells in ultra-low power Integrated Circuits (ICs) based on nanoscale Complementary Metal Oxide Semiconductor (CMOS) devices are likely to be the most vulnerable to large-scale soft errors. Conventional error correction circuits may not be able to handle the distributed nature of such errors and are susceptible to soft errors themselves. In this thesis, a distributed error correction circuit called Self-Healing Cellular Automata (SHCA) that can repair itself is presented. A possible way to deploy a SHCA in a system of SRAM-based embedded program memories (ePM) for one type of chip multi-processors is also discussed. The …

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.

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 …

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 …

Analysis And Design Of Earthquake Relief Virtual Logistic Information System, Chi Chen

World Maritime University Dissertations

No abstract provided.

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 …

Jdiet: Footprint Reduction For Memory-Constrained Systems, Michael John Huffman

Master's Theses

Main memory remains a scarce computing resource. Even though main memory is becoming more abundant, software applications are inexorably engineered to consume as much memory as is available. For example, expert systems, scientific computing, data mining, and embedded systems commonly suffer from the lack of main memory availability.

This thesis introduces JDiet, an innovative memory management system for Java applications. The goal of JDiet is to provide the developer with a highly configurable framework to reduce the memory footprint of a memory-constrained system, enabling it to operate on much larger working sets. Inspired by buffer management techniques common in modern …

A Video Manager, Nicholas Omann

Honors Capstones

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

Anticipating Technological Change: Predictions, Trends And Gadgets, Carol A. Watson

Presentations

With the current economic downtown, today's business environment is more competitive than ever. Businesses that distinguish themselves in any small way and provide cost-savings, can gain a significant advantage over their rivals. To emphasize the point, note that the ABA Techshow 2009 has a session titled: If You’re Not Serving Your Clients Online, Someone Else Will Be. It is, therefore, essential that attorneys harness technology and remain up-to-date on the latest computer developments . In this paper, I will begin by discussing technologies that are currently available on the web that will increase your abilities to collaborate, reduce your office …

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 …

Chip To Chip Optical Interconnection Using Mems Mirrors, Tod V. Laurvick

Theses and Dissertations

This experiment explores the use of MEMS mirrors to direct subsurface optical signals to another device and reception of those signals for use in chip to chip communications. Devices were built in PolyMUMPs to control horizontal and vertical beam direction and tilting in the outgoing signal and MEMS beam splitters for the incoming signal. Several elements of the outgoing beam path were successful and those which needed improvement indicate a high probability of success with limited trials needed and currently successful design elements could still be improved within the scope of PolyMUMPs. The incoming beam path elements were not successful …

Biomedical Informatics Research Network (Birn) Data Repository, Laurence Jonathan Bouts Bohannan

Theses Digitization Project

The primary goal of this project was to streamline the submission process for researchers to categorize, approve, curate, and publish these data sets. By supporting the sharing and exchange of these data types in fulfillment of the National Institute of Health guidelines the BIRN Data Repository will have the ability to grow as the need develops for these researchers to easily share information.