Computer Engineering Commons^™

High Performance Text Document Clustering, Yanjun Li

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Data mining, also known as knowledge discovery in database (KDD), is the process to discover interesting unknown knowledge from a large amount of data. Text mining is to apply data mining techniques to extract interesting and nontrivial information and knowledge from unstructured text. Text clustering is one of important techniques of text mining, which is the unsupervised classification of similar documents into different groups.

This research focuses on improving the performance of text clustering. We investigated the text clustering algorithms in four aspects: document representation, documents closeness measurement, high dimension reduction and parallelization. We propose a group of high performance …

An Analysis Of Neutral Drift's Effect On The Evolution Of A Ctrnn Locomotion Controller With Noisy Fitness Evaluation, Gregory Robert Kramer

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This dissertation focuses on the evolution of Continuous Time Recurrent Neural Networks (CTRNNs) as controllers for control systems. Existing research suggests that the process of neutral drift can greatly benefit evolution for problems whose fitness landscapes contain large-scale neutral networks. CTRNNs are known to be highly degenerate, providing a possible source of large-scale landscape neutrality, and existing research suggests that neutral drift benefits the evolution of simple CTRNNs. However, there has been no in-depth examination of the effects of neutral drift on complex CTRNN controllers, especially in the presence of noisy fitness evaluation. To address this problem, this dissertation presents …

Computational Methods For The Objective Review Of Forensic Dna Testing Results, Jason R. Gilder

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Since the advent of criminal investigations, investigators have sought a "gold standard" for the evaluation of forensic evidence. Currently, deoxyribonucleic acid (DNA) technology is the most reliable method of identification. Short Tandem Repeat (STR) DNA genotyping has the potential for impressive match statistics, but the methodology not infallible. The condition of an evidentiary sample and potential issues with the handling and testing of a sample can lead to significant issues with the interpretation of DNA testing results. Forensic DNA interpretation standards are determined by laboratory validation studies that often involve small sample sizes. This dissertation presents novel methodologies to address …

Summaritive Digest For Large Document Repositories With Application To E-Rulemaking, Lijun Chen

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Large document repositories need to be organized and summarized to make them more accessible and understandable. Such needs exist in many applications, including web search, e-rulemaking (electronic rulemaking) and document archiving. Even though much has been done in the areas of document clustering and summarization, there are still many new challenges and issues that need to be addressed as the repositories become larger, more prevalent and dynamic. In this dissertation, we investigate more informative ways to organize and summarize large document repositories, especially e-rulemaking feedback repositories (ERFRs), so that the large repositories can be managed and digested more efficiently and …

Comparative Microarray Data Mining, Shihong Mao

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As a revolutionary technology, microarrays have great potential to provide genome-wide patterns of gene expression, to make accurate medical diagnosis, and to explore genetic causes underlying diseases. It is commonly believed that suitable analysis of microarray datasets can lead to achieve the above goals. While much has been done in microarray data mining, few previous studies, if any, focused on multiple datasets at the comparative level. This dissertation aims to fill this gap by developing tools and methods for set-based comparative microarray data mining. Specifically, we mine highly differentiative gene groups (HDGGs) from given datasets/classes, evaluate the concordance of datasets …

A Hybrid Approach To Retrieving Web Documents And Semantic Web Data, Trivikram Immaneni

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The Semantic Web has been evolving into a property-linked web of RDF data, conceptually divorced from (but physically housed in) the World Wide Web of hyperlinked documents. Data Retrieval techniques are typically used to retrieve data from the Semantic Web while Information Retrieval techniques are used to retrieve documents from the Hypertext Web. Conceptually unifying the two webs enables the exploitation of their interconnections resulting in benefits to both data and document retrieval. Towards this end, we present the Unified Web model that integrates the two webs and formalizes the structure and the semantics of their interconnections. We present a …

Bibliography Tools In The Context Of Www And Latex, Munushree Thummala

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Preparation of academic papers involves not only the creative processes but also the more mechanical tasks such as adjusting the form and style to suit the demands of the publishing journal or conference. Among several packages that help in these rather tedious mechanical tasks, the TEX + LATEX + BibTEX combination is extremely popular. This thesis is about tools that help in the necessary task of citing related work accurately. It focuses on three aspects of this larger bibliography frame work: (i) a survey of existing bibliography formats and tools, (ii) a database view of BibTEX files and functionality that …

Investigating The Male-Driven Evolution Hypothesis Using Human AluRepeat Elements, Sridhar Ramachandran

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Thousands of copies of short interspersed repeats (SINEs) are scattered essentially ran-domly through the human genome. Although copies of each repeat subfamily are identical at the time of their insertion, they become subject to individual substitutions after insertion. As the relative time of insertion is known for many of these repeats, such "junk DNA" can be used to provide a sizeable number of time-series data points for studying substitution effects in a variety of genomic contexts. This dissertation specifically discusses the usefulness of the Alufamily of SINE repeats towards addressing open problems in genomics, population genetics, and biology in …

A Formal Language Approach For Detecting Texture Paths And Patterns In Images, Prithviraj S. Patil

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This Master thesis considers the use of formal languages representation for image processing, especially texture patterns and determining texture paths in them. The texture paths are detected and extracted by using image processing techniques, such as image segmentation to isolate regions of interest, and then the extraction of repeating textures. The detection of the texture blocks is obtained by recursively using 27 X 27, 9 X 9, and 3 X 3 windows. Predefined repeating texture patterns are also searched for in each of the sets. For each set of texture blocks with similar or same characteristics, curve fitting techniques are …

Simulation And Analysis Of Rfid Localization Algorithms, Zubin Shah

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Radio frequency identification (RFID) based localization systems provide a unique approach to localize mobile entities equipped with RFID readers or tagged with RFID tags. UHF RFID systems using passive tags are a good choice considering their cost, reading range, and reliability. With global acceptance and deployment of UHF RFID systems using passive tags for tracking and identification, virtually everything around us can be tagged with small and low-cost passive RFID tags. This thesis describes a Monte Carlo Localization based algorithm to localize a mobile RFID reader within a tagged environment. A software tool is developed to validate this localization process, …

A Field Programmable Gate Array Architecture For Two-Dimensional Partial Reconfiguration, Fei Wang

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Reconfigurable machines can accelerate many applications by adapting to their needs through hardware reconfiguration. Partial reconfiguration allows the reconfiguration of a portion of a chip while the rest of the chip is busy working on tasks. Operating system models have been proposed for partially reconfigurable machines to handle the scheduling and placement of tasks. They are called OS4RC in this dissertation. The main goal of this research is to address some problems that come from the gap between OS4RC and existing chip architectures and the gap between OS4RC models and practical applications. Some existing OS4RC models are based on an …

Pattern Recognition Via Machine Learning With Genetic Decision-Programming, Carl C. Hoff

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In the intersection of pattern recognition, machine learning, and evolutionary computation is a new search technique by which computers might program themselves. That technique is called genetic decision-programming. A computer can gain the ability to distinguish among the things that it needs to recognize by using genetic decision-programming for pattern discovery and concept learning. Those patterns and concepts can be easily encoded in the spines of a decision program (tree or diagram). A spine consists of two parts: (1) the test-outcome pairs along a path from the program's root to any of its leaves and (2) the conclusion in that …