Latest content added for UNT Digital Library Collection: UNT Theses and Dissertationshttp://digital.library.unt.edu/explore/collections/UNTETD/browse/?fq=untl_institution:UNT&fq=str_degree_department:Department+of+Computer+Science2014-03-26T09:30:20-05:00UNT LibrariesThis is a custom feed for browsing UNT Digital Library Collection: UNT Theses and DissertationsA Unifying Version Model for Objects and Schema in Object-Oriented Database System2014-03-26T09:30:20-05:00http://digital.library.unt.edu/ark:/67531/metadc279222/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc279222/"><img alt="A Unifying Version Model for Objects and Schema in Object-Oriented Database System" title="A Unifying Version Model for Objects and Schema in Object-Oriented Database System" src="http://digital.library.unt.edu/ark:/67531/metadc279222/thumbnail/"/></a></p><p>There have been a number of different versioning models proposed. The research in this area can be divided into two categories: object versioning and schema versioning. In this dissertation, both problem domains are considered as a single unit. This dissertation describes a unifying version model (UVM) for maintaining changes to both objects and schema. UVM handles schema versioning operations by using object versioning techniques. The result is that the UVM allows the OODBMS to be much smaller than previous systems. Also, programmers need know only one set of versioning operations; thus, reducing the learning time by half. This dissertation shows that UVM is a simple but semantically sound and powerful version model for both objects and schema.</p>Multiresolutional/Fractal Compression of Still and Moving Pictures2014-03-26T09:30:20-05:00http://digital.library.unt.edu/ark:/67531/metadc278779/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278779/"><img alt="Multiresolutional/Fractal Compression of Still and Moving Pictures" title="Multiresolutional/Fractal Compression of Still and Moving Pictures" src="http://digital.library.unt.edu/ark:/67531/metadc278779/thumbnail/"/></a></p><p>The scope of the present dissertation is a deep lossy compression of still and moving grayscale pictures while maintaining their fidelity, with a specific goal of creating a working prototype of a software system for use in low bandwidth transmission of still satellite imagery and weather briefings with the best preservation of features considered important by the end user.</p>A Machine Learning Method Suitable for Dynamic Domains2014-03-26T09:30:20-05:00http://digital.library.unt.edu/ark:/67531/metadc278720/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278720/"><img alt="A Machine Learning Method Suitable for Dynamic Domains" title="A Machine Learning Method Suitable for Dynamic Domains" src="http://digital.library.unt.edu/ark:/67531/metadc278720/thumbnail/"/></a></p><p>The efficacy of a machine learning technique is domain dependent. Some machine learning techniques work very well for certain domains but are ill-suited for other domains. One area that is of real-world concern is the flexibility with which machine learning techniques can adapt to dynamic domains. Currently, there are no known reports of any system that can learn dynamic domains, short of starting over (i.e., re-running the program). Starting over is neither time nor cost efficient for real-world production environments. This dissertation studied a method, referred to as Experience Based Learning (EBL), that attempts to deal with conditions related to learning dynamic domains. EBL is an extension of Instance Based Learning methods. The hypothesis of the study related to this research was that the EBL method would automatically adjust to domain changes and still provide classification accuracy similar to methods that require starting over. To test this hypothesis, twelve widely studied machine learning datasets were used. A dynamic domain was simulated by presenting these datasets in an uninterrupted cycle of train, test, and retrain. The order of the twelve datasets and the order of records within each dataset were randomized to control for order biases in each of ten runs. As a result, these methods provided datasets that represent extreme levels of domain change. Using the above datasets, EBL's mean classification accuracies for each dataset were compared to the published static domain results of other machine learning systems. The results indicated that the EBL's system performance was not statistically different (p>0.30) from the other machine learning methods. These results indicate that the EBL system is able to adjust to an extreme level of domain change and yet produce satisfactory results. This finding supports the use of the EBL method in real-world environments that incur rapid changes to both variables and values.</p>Computational Complexity of Hopfield Networks2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc278272/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278272/"><img alt="Computational Complexity of Hopfield Networks" title="Computational Complexity of Hopfield Networks" src="http://digital.library.unt.edu/ark:/67531/metadc278272/thumbnail/"/></a></p><p>There are three main results in this dissertation. They are PLS-completeness of discrete Hopfield network convergence with eight different restrictions, (degree 3, bipartite and degree 3, 8-neighbor mesh, dual of the knight's graph, hypercube, butterfly, cube-connected cycles and shuffle-exchange), exponential convergence behavior of discrete Hopfield network, and simulation of Turing machines by discrete Hopfield Network.</p>Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc278231/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278231/"><img alt="Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment" title="Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment" src="http://digital.library.unt.edu/ark:/67531/metadc278231/thumbnail/"/></a></p><p>Genetic algorithm and artificial life techniques are applied to the development of challenging and interesting opponents in a combat-based computer game. Computer simulations are carried out against an idealized human player to gather data on the effectiveness of the computer generated opponents.</p>Exon/Intron Discrimination Using the Finite Induction Pattern Matching Technique2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc277629/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc277629/"><img alt="Exon/Intron Discrimination Using the Finite Induction Pattern Matching Technique" title="Exon/Intron Discrimination Using the Finite Induction Pattern Matching Technique" src="http://digital.library.unt.edu/ark:/67531/metadc277629/thumbnail/"/></a></p><p>DNA sequence analysis involves precise discrimination of two of the sequence's most important components: exons and introns. Exons encode the proteins that are responsible for almost all the functions in a living organism. Introns interrupt the sequence coding for a protein and must be removed from primary RNA transcripts before translation to protein can occur.
A pattern recognition technique called Finite Induction (FI) is utilized to study the language of exons and introns. FI is especially suited for analyzing and classifying large amounts of data representing sequences of interest. It requires no biological information and employs no statistical functions. Finite Induction is applied to the exon and intron components of DNA by building a collection of rules based upon what it finds in the sequences it examines. It then attempts to match the known rule patterns with new rules formed as a result of analyzing a new sequence. A high number of matches predict a
probable close relationship between the two sequences; a low number of matches signifies a large amount of difference between the two. This research demonstrates FI to be a viable tool for measurement when known patterns are available for the formation of rule sets.</p>Symplectic Integration of Nonseparable Hamiltonian Systems2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc278485/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278485/"><img alt="Symplectic Integration of Nonseparable Hamiltonian Systems" title="Symplectic Integration of Nonseparable Hamiltonian Systems" src="http://digital.library.unt.edu/ark:/67531/metadc278485/thumbnail/"/></a></p><p>Numerical methods are usually necessary in solving Hamiltonian systems since there is often no closed-form solution. By utilizing a general property of Hamiltonians, namely the symplectic property, all of the qualities of the system may be preserved for indefinitely long integration times because all of the integral (Poincare) invariants are conserved. This allows for more reliable results and frequently leads to significantly shorter execution times as compared to conventional methods. The resonant triad Hamiltonian with one degree of freedom will be focused upon for most of the numerical tests because of its difficult nature and, moreover, analytical results exist whereby useful comparisons can be made.</p>A Theoretical Network Model and the Incremental Hypercube-Based Networks2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc277860/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc277860/"><img alt="A Theoretical Network Model and the Incremental Hypercube-Based Networks" title="A Theoretical Network Model and the Incremental Hypercube-Based Networks" src="http://digital.library.unt.edu/ark:/67531/metadc277860/thumbnail/"/></a></p><p>The study of multicomputer interconnection networks is an important area of research in parallel processing. We introduce vertex-symmetric Hamming-group graphs as a model to design a wide variety of network topologies including the hypercube network.</p>Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc278153/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc278153/"><img alt="Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design" title="Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design" src="http://digital.library.unt.edu/ark:/67531/metadc278153/thumbnail/"/></a></p><p>The goal of a parallel algorithm is to solve a single problem using multiple processors working together and to do so in an efficient manner. In this regard, there is a need to categorize strategies in order to solve broad classes of problems with similar structures and requirements. In this dissertation, two parallel algorithm design strategies are considered: linked list ranking and parentheses matching.</p>Using Normal Deduction Graphs in Common Sense Reasoning2014-03-24T20:07:29-05:00http://digital.library.unt.edu/ark:/67531/metadc277922/<p><a href="http://digital.library.unt.edu/ark:/67531/metadc277922/"><img alt="Using Normal Deduction Graphs in Common Sense Reasoning" title="Using Normal Deduction Graphs in Common Sense Reasoning" src="http://digital.library.unt.edu/ark:/67531/metadc277922/thumbnail/"/></a></p><p>This investigation proposes a powerful formalization of common sense knowledge based on function-free normal deduction graphs (NDGs) which form a powerful tool for deriving Horn and non-Horn clauses without functions. Such formalization allows common sense reasoning since it has the ability to handle not only negative but also incomplete information.</p>