You limited your search to:

  Partner: UNT Libraries
 Department: Department of Computer Science
 Language: English
 Collection: UNT Theses and Dissertations
A Programming Language For Concurrent Processing

A Programming Language For Concurrent Processing

Date: August 1972
Creator: Jackson, Portia M.
Description: This thesis is a proposed solution to the problem of including an effective interrupt mechanism in the set of concurrent- processing primitives of a block-structured programming language or system. The proposed solution is presented in the form of a programming language definition and model. The language is called TRIPLE.
Contributing Partner: UNT Libraries
Using Normal Deduction Graphs in Common Sense Reasoning

Using Normal Deduction Graphs in Common Sense Reasoning

Date: May 1992
Creator: Munoz, Ricardo A. (Ricardo Alberto)
Description: 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.
Contributing Partner: UNT Libraries
Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design

Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design

Date: December 1993
Creator: Halverson, Ranette Hudson
Description: 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.
Contributing Partner: UNT Libraries
Multiresolutional/Fractal Compression of Still and Moving Pictures

Multiresolutional/Fractal Compression of Still and Moving Pictures

Date: December 1993
Creator: Kiselyov, Oleg E.
Description: 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.
Contributing Partner: UNT Libraries
Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment

Intrinsic and Extrinsic Adaptation in a Simulated Combat Environment

Date: May 1995
Creator: Dombrowsky, Steven P. (Steven Paul)
Description: 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.
Contributing Partner: UNT Libraries
A Theoretical Network Model and the Incremental Hypercube-Based Networks

A Theoretical Network Model and the Incremental Hypercube-Based Networks

Date: May 1995
Creator: Mao, Ai-sheng
Description: 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.
Contributing Partner: UNT Libraries
Practical Cursive Script Recognition

Practical Cursive Script Recognition

Date: August 1995
Creator: Carroll, Johnny Glen, 1953-
Description: This research focused on the off-line cursive script recognition application. The problem is very large and difficult and there is much room for improvement in every aspect of the problem. Many different aspects of this problem were explored in pursuit of solutions to create a more practical and usable off-line cursive script recognizer than is currently available.
Contributing Partner: UNT Libraries
Convexity-Preserving Scattered Data Interpolation

Convexity-Preserving Scattered Data Interpolation

Date: December 1995
Creator: Leung, Nim Keung
Description: Surface fitting methods play an important role in many scientific fields as well as in computer aided geometric design. The problem treated here is that of constructing a smooth surface that interpolates data values associated with scattered nodes in the plane. The data is said to be convex if there exists a convex interpolant. The problem of convexity-preserving interpolation is to determine if the data is convex, and construct a convex interpolant if it exists.
Contributing Partner: UNT Libraries
Symplectic Integration of Nonseparable Hamiltonian Systems

Symplectic Integration of Nonseparable Hamiltonian Systems

Date: May 1996
Creator: Curry, David M. (David Mason)
Description: 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.
Contributing Partner: UNT Libraries
A Machine Learning Method Suitable for Dynamic Domains

A Machine Learning Method Suitable for Dynamic Domains

Date: July 1996
Creator: Rowe, Michael C. (Michael Charles)
Description: 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. ...
Contributing Partner: UNT Libraries
FIRST PREV 1 2 3 4 5 NEXT LAST